Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 and 3-15 are rejected under 35 USC 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites
A causal relation inference device comprising: a processor configured to execute a program; and a storage device storing the program, wherein the processor is configured to
execute a first calculation process of calculating an internal vector based on a feature vector of a plurality of samples and a first learning parameter, the plurality of samples being patients
a second calculation process of calculating a reallocation vector based on a second learning parameter
and the internal vector calculated by the first calculation process, and a third calculation process of calculating a pointwise weight vector for each of the plurality of samples based on a third learning parameter
and the reallocation vector calculated by the second calculation process.
and execute a fourth calculation process of calculating, for each sample, a prediction value for an assignment variable to be assigned to the sample, based on the feature vector and the pointwise weight vector calculated by the third calculation process.
(emphasis added). Examiner finds the emphasized portions of claim 1 above recite an abstract idea—namely, mathematical concepts in the form of relationships, formulas and/or equations, and/or calculations. . See MPEP 2106.04(a)(2)(I) and (A)-(C)
The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations.
. . .
A. Mathematical Relationships
A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols. For example, pressure (p) can be described as the ratio between the magnitude of the normal force (F) and area of the surface on contact (A), or it can be set forth in the form of an equation such as p = F/A.
. . .
B. Mathematical Formulas or Equations
A claim that recites a numerical formula or equation will be considered as falling within the "mathematical concepts" grouping. In addition, there are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.
. . .
C. Mathematical Calculations
A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.
. . .
When read as a whole, the recited limitations are directed to mathematical formulas, relationships, and/or mathematical calculations.
wing analysis:
Bolded Abstract Idea Claim Elements
Examiner analysis of bolded abstract idea elements considered individually
Relevant MPEP sections
A causal relation inference device comprising: a processor configured to execute a program; and a storage device storing the program, wherein the processor is configured to execute
a first calculation process of calculating an internal vector based on a feature vector of a plurality of samples and a first learning parameter, the plurality of samples being patients
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See Applicant’s specification (Spec) p. 13-15, Fig. 4, equations 1-3. The recited “patient samples” element does not alter the above analysis. It merely describes the data used to perform the calculation.
2106.04(a)(2)(I)(A)(B)(C)
a second calculation process of calculating a reallocation vector based on a second learning parameter
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See Spec p. 13-15, Fig. 4, equations 1-3
Id.
and the internal vector calculated by the first calculation process,
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See Spec p. 13-15, Fig. 4, equations 1-3
Id.
and a third calculation process of calculating a pointwise weight vector for each of the plurality of samples based on a third learning parameter
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations.. See Spec p. 13-15, Fig. 4, equations 1-3
Id.
and the reallocation vector calculated by the second calculation process.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See Spec p. 13-15, Fig. 4, equations 1-3
Id.
and execute a fourth calculation process of calculating, for each sample, a prediction value for an assignment variable to be assigned to the sample, based on the feature vector and the pointwise weight vector calculated by the third calculation process.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations.. See, e.g. Spec pp. 13-16 equations 1-4.
Turning to the additional elements and whether they integrate the exception, Examiner provides the following analysis:
Italicized Additional elements
Examiner analysis of italicized additional elements and whether they integrate the exception.
Relevant MPEP sections
A causal relation inference device comprising: a processor configured to execute a program;
This element recites mere instructions to apply the exception. The elements are recited at a high level of generality and such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, this additional element does not integrate the exception.
2106.05(f)
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
and a storage device storing the program, wherein the processor is configured to execute
This element recites mere instructions to apply the exception. The elements are recited at a high level of generality and such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, this additional element does not integrate the exception.
Id.
Turning to the additional elements and whether they recite an inventive concept, Examiner provides the following analysis:
Italicized Additional Elements
Examiner Analysis Of Italicized Additional Elements and Whether They Recite An Inventive Concept
Relevant MPEP Sections
A causal relation inference device comprising: a processor configured to execute a program;
This element recites mere instructions to apply the exception. The elements are recited at a high level of generality and such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not recite an inventive concept.
2106.05(f)
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
and a storage device storing the program, wherein the processor is configured to execute
This element recites mere instructions to apply the exception. The elements are recited at a high level of generality and such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not recite an inventive concept.
Id.
Claim 14 is also rejected for the reasons given above for claim 1. Additionally, “14. A causal relation inference method using a causal relation inference device, the causal relation inference device including a processor configured to execute a program and a storage device storing the program, the causal relation inference method comprising: causing the processor to execute. . . “ recite mere instructions to apply the exception and thus these elements do not integrate the exception or provide an inventive concept.
Claim 15 is also rejected for the reasons given above for claim 1. Additionally, “15. A non-transitory processor-readable recording medium having recorded thereon a causal relation inference program to be executed by a processor, the causal relation inference program causing the processor to execute: . . “ recite mere instructions to apply the exception and thus these elements do not integrate the exception or provide an inventive concept.
The additional elements above “[a]dd nothing … that is not already present when the steps are considered separately’”. MPEP 2106.05 (I)(B)(quoting Alice). When read as a whole, the recited limitations are directed to mathematical formulas, relationships, and/or mathematical calculations performed, for example, when using or training a deep neural network (DNN). As such, when the claim elements are considered as a whole and individually, claim 1 recites an abstract idea without significantly more1.
Dependent claims 3-11 are rejected under 35 USC 101 for the reasons indicated below.
Claim (abstract idea elements in bold; additional elements not bolded)
Analysis
MPEP
3. The causal relation inference device according to claim 1, wherein the processor is configured to execute an update process of updating the first learning parameter, the second learning parameter, and the third learning parameter by using the assignment variable and the prediction value for the assignment variable calculated by the fourth calculation process,
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 13-16 equations 1-4. The “update process” is nothing more than mathematical calculations and using mathematical formulas when read broadly in light of the specification. See spec at p. 16-17 and 32.
Id.
in the first calculation process, the processor calculates the internal vector based on the feature vector and the first learning parameter updated by the update process,
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 13-16 equations 1-4.
2106.04(a)(2)(I)(A)(B)(C)
in the second calculation process, the processor calculates the reallocation vector based on the internal vector and the second learning parameter updated by the update process, and in the third calculation process, the processor calculates the pointwise weight vector based on the reallocation vector and the third learning parameter updated by the update process.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 13-16 equations 1-4.
Id.
and in the third calculation process, the processor calculates the pointwise weight vector based on the reallocation vector and the third learning parameter updated by the update process.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 13-16 equations 1-4. The “update process” is nothing more than mathematical calculations and using mathematical formulas. See spec at p. 16-17 and 32.
Id.
4. The causal relation inference device according to claim 1, wherein the processor is configured to execute a fifth calculation process of calculating an effect obtained by the plurality of samples, based on the prediction value for the assignment variable calculated by the fourth calculation process for each of the plurality of samples, the assignment variable, and a result obtained by the sample in the assignment variable.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 13-17 equations 1-5.
Id.
5. The causal relation inference device according to claim 4, wherein the processor is configured to execute a clustering process of clustering the plurality of samples,
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations.. See, e.g. Spec p. 17 (Examiner finds K-means clustering, for example, is nothing but mathematical calculations via formulas and equations that represent mathematical relationships between variables).
Id.
and wherein in the fifth calculation process, the processor calculates, for each of a plurality of sample populations obtained by the clustering process, an effect obtained by the sample population, based on the prediction value for the assignment variable, the assignment variable, and the result obtained by the sample in the assignment variable.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec p. 17 (Examiner finds K-means clustering, for example is nothing but mathematical calculations via formulas and equations and mathematical relationships between variables). See Spec. p. 16 equation 5 (fifth calculation (equation/calculation).
Id.
6. The causal relation inference device according to claim 5, wherein in the clustering process, the processor clusters the plurality of samples based on the reallocation vector.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 17-18. Examiner finds K-means clustering, for example, is nothing but mathematical calculations using mathematical formulas/equations. The result of these calculations represent nothing more than relationships between variables). See Spec. pp. 14-15 equation 2 (reallocation vector mathematical calculation).
Id.
7. The causal relation inference device according to claim 1, wherein the processor is configured to execute a sixth calculation process of generating, based on a distance between a first sample whose value of the assignment variable is a first assignment value among the plurality of samples and a second sample whose value of the assignment variable is a second assignment value among the plurality of samples, a pair of the first sample and the second sample, and calculating, in the pair, an effect obtained by the plurality of samples, based on a first result obtained by the first sample at the first assignment value and a second result obtained by the second sample at the second assignment value.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations.. See, e.g. Spec pp. 13-16 and equations 1-4; Spec p. 18-19 and equation 6.
Id.
8. The causal relation inference device according to claim 7, wherein the processor is configured to execute a clustering process of clustering the plurality of samples, and wherein in the sixth calculation process, the processor generates, for each of a plurality of sample populations obtained by the clustering process, the pair of the first sample and the second sample, and calculates, in the pair, an effect obtained by the sample population, based on the first result and the second result.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations.. See, e.g. Spec .pp. 14-15 equation 2 Spec p. 18-19 and equation 6.
Id.
9. The causal relation inference device according to claim 7, wherein in the sixth calculation process, the processor generates the pair based on a distance between the reallocation vector of the first sample and the reallocation vector of the second sample.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec p. 18-19 and equation 6.
Id.
10. The causal relation inference device according to claim 1, wherein the processor is configured to execute a seventh calculation process of calculating, for each of the plurality of samples, an importance vector indicating an importance of the feature vector.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 19-20 and equation 7.
Id.
11. The causal relation inference device according to claim 10, wherein the processor is configured to execute a clustering process of clustering the plurality of samples, and in the seventh calculation process, the processor calculates the importance vector for each of a plurality of sample populations obtained by the clustering process.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec pp. 19-20 and equation 7.
See, e.g. Spec pp. 17-18 (Examiner finds K-means clustering, for example, is nothing but mathematical calculations using mathematical formulas/equations. The result of these calculations represent nothing more than relationships between variables).
Id.
12. The causal relation inference device according to claim 1, wherein the assignment variable indicates treatment for the sample.
This element, when read broadly in light of the specification, is directed to a mathematical concept in the form of mathematical relationships, mathematical calculations, and/or mathematical formulas or equations. See, e.g. Spec p. 11 (“In addition, the neural network 200 calculates, by a product-sum operation 226 of the feature vector 201 and the pointwise weight vector 206, a prediction value 207 for an assignment variable Z.sub.(n) indicating a predetermined action for each patient n, for example, the presence or absence of treatment, that is, the propensity score 152.”)
Id.
13. The causal relation inference device according to claim 4, wherein the effect obtained by the sample is a therapeutic effect.
This element generally links the abstract idea to the field of use of medicine/therapy and thus does not integrate the exception or recite an inventive concept.
2106.05(h)
With respect to the additional elements not specifically analyzed above, the language “The causal relation inference device according to” and “processor configured to. . . .” recite mere instructions to apply the abstract idea on a computer and thus they do not integrate the exception or recite an inventive concept. See MPEP 2106.05(f).
The additional elements above “[a]dd nothing … that is not already present when the steps are considered separately’”. MPEP 2106.05 (I)(B)(quoting Alice). When read as a whole, the recited limitations are directed to mathematical formulas, relationships, and/or mathematical calculations performed, for example, when using or training a deep neural network (DNN). As such, the dependent claim elements above “[a]dd nothing … that is not already present when the steps are considered separately’”. MPEP 2106.05 (I)(B)(quoting Alice).
Thus, when the claim elements above are considered as a whole and individually, claims 3-13 recite an abstract idea without significantly more.
Response to Arguments
Applicant argues
Applicant respectfully submits that at least Applicant's independent claims 1, 14 and 15, as presented herein, are directed to patent-eligible subject matter under 35 U.S.C. § 101 for at least the following reasons.
When considering claim 1 as a whole, as required, the claim sets forth an improvement to the field of estimating efficacy of a medical therapy or a drug by improving how propensity scores (i.e., assignment variables) indicating a probability that a patient belongs to a treatment group are inferred
Examiner respectfully disagrees. When considered as a whole, the claimed invention recites mathematical concepts without significantly more. The claimed invention explicitly recites four calculations. These calculations are clearly mathematical concepts when read broadly in light of the specification. See, e.g. Spec pp. 13-16 equations 1-4. The additional general purpose computer components do not reflect an improvement disclosed in the specification. They are mere instructions to apply the exception. The addition of “patient samples” in the claim does not cause the claim to be patent eligible. The patient samples are merely the data upon which calculations are performed.
Applicant further argues
Consideration of improvements is relevant to the eligibility analysis regardless of the technology of the claimed invention. That is, the consideration applies equally whether it is a computer-implemented invention, an invention in the life sciences, or any other technology.
See, e.g., Rapid Litigation Management v. CellzDirect, Inc., 827 F.3d 1042, 119 USPQ2d 1370 (Fed. Cir. 2016).
MPEP Section 2106.05(a) II (emphasis added).
The improvement is a technical solution to a technical problem, as explained in the specification.
In order to accurately estimate an effect of a therapy or a drug, it is necessary to compare a case of performing therapeutic or drug treatment on the same patient with a case of not performing the therapeutic or drug treatment. However, there are cases where it is impossible to perform experiments in which an operation with and an operation without administration are repeated to the same patient, such as anticancer drug treatment with strong side effects. Therefore, there is a method referred to as propensity score analysis as a method of estimating the treatment effect for convenience by comparing a patient group on which the treatment is performed and a patient group on which the treatment is not performed. With the propensity score analysis, the treatment effect can be estimated by comparing similar patients in the treatment group and the non-treatment group.
A propensity score is a value indicating a probability that a patient belongs to the treatment group. By estimating the effect of treatment or administration for patients with similar tendencies in belonging to the
treatment group, it is possible to estimate an effect similar to that of a case of performing treatment on the same patient. Generally, a statistical method referred to as logistic regression is used as a method for calculating the propensity score, but it is difficult to identify similar patients since prediction accuracy of the logistic repression is low.
Deep Learning (neural network) is one of techniques for implementing artificial intelligence (Al). With Deep Learning, high prediction accuracy can be achieved. Each element of a feature vector, which is an input item used for prediction, is subjected to a weighted product-sum operation with other elements each time the element passes through a plurality of perceptrons. Therefore, it is difficult in principle to know importance of each element of the feature vector. This is a fatal drawback when Deep Learning is used in a medical field.
Paras. [0003] - [0005] of the pre-grant publication corresponding to the present application (US 2023/0065173) (emphasis added).
There are no additional elements in the claims that reflect this disclosed improvement.
Applicant further argues
Accordingly, the presently claimed invention provides a technical solution to the above-mentioned problems by inferring a value of an assignment variable with high accuracy. See paras. [0014] and [0100].
The inference is nothing more than a result of mathematical calculations. A mathematical calculation, without more, cannot integrate the abstract idea into a practical application. See MPEP 2106.05. (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”).
Applicant further argues
That is, the presently claimed invention sets forth a computer-implemented specific technical processes under technically relevant conditions.
The claimed invention recited in the independent claims recite four mathematical concepts configured to be executed on a general purpose computer. That the calculations are performed on a general purpose computer do not make them patent eligible. See MPEP 2106.04(a)(2)(III)(C) (“A Claim That Requires a Computer May Still Recite a Mental Process”). Thus, the claimed invention is directed to an abstract
idea without significantly more.
Applicant argues
The improvement is also recited in the claims. For example, claim 1 recites "a first calculation process of calculating an internal vector based on a feature vector of a plurality of samples and a first learning parameter, the plurality of samples being patients, ... execute a fourth calculation process of calculating, for each sample, a prediction value for an assignment variable to be assigned to the sample, based on the feature vector and the pointwise weight vector calculated by the third calculation process."
When read broadly in light of the specification, these calculations are nothing more than mathematical concepts. See above 101 rejection. A mathematical concept cannot integrate the abstract idea into a practical application. See MPEP 2106.05. (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”). This argument is therefore not persuasive.
Applicant further argues
The MPEP also states:
In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP § 2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018)).
The additional elements in the claim are nothing more than general purpose computing components. Examiner finds these general purpose computer elements along with the recited mathematical calculations are equivalent to “apply the abstract idea on a computer” and thus, even when they are considered together, these elements fail to integrate the exception and do not recite an inventive concept. See MPEP 2106.05(f). As indicated above, “. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”). MPEP 2106.05.
Applicant argues
Thus, it is important for examiners to analyze the claim as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or technical field.
When considered as a whole, the claimed invention recites a general purpose computer configured to perform four mathematical concepts. There are no additional elements that reflect an improvement in the specification. The recited mathematical concepts, by themselves, cannot be a basis of the improvement. See MPEP 2105.05. The general purpose computer elements are mere instructions to apply the exception and thus they do not integrate the exception and they do not recite an inventive concept. That the calculations are performed on a general purpose computer do not make them patent eligible. See MPEP 2106.04(a)(2)(III)(C) (“A Claim That Requires a Computer May Still Recite a Mental Process”). Thus, the claimed invention is directed to an abstract
idea without significantly more and Applicant’s argument is not persuasive.
Applicant argues
Even further, the improvement set forth in claim 1 is not to the alleged abstract idea itself and is not improvement to a mathematical concept.
Claim 1 recites four mathematical concepts configured to be executed on general purpose computer. It is clear the claims are directed to “improved mathematical concepts” when the claims are read broadly in light of the specification. See, e.g. Spec pp. 13-16 equations 1-4. Applicant’s assertion to the contrary is not persuasive.
Applicant further argues
Additionally, this is not a case like Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 216, 110 USPQ2d 1976, 1980 (2014) where the computer is merely used as a tool to perform an existing process.
Examiner agrees the computer is not being used to perform an existing mathematical calculations/concepts. However, the claimed invention is nevertheless ineligible. The claimed invention recites four mathematical concepts configured to be performed on a general purpose computer. Mathematical concepts are not patent eligible and the additional, general purpose computer components are equivalent to “apply it.” See above and MPEP 2106.05(f). As such, the claimed invention recites an abstract idea without significantly more.
Applicant further argues
Thus, Applicant's claim 1 is not directed to an abstract idea because claim 1 includes additional elements that integrate the alleged abstract idea into a practical application of the abstract idea demonstrated by a particular improvement to the field of estimating efficacy of a medical therapy or a drug by improving how propensity scores (i.e., assignment variables) indicating a probability that a patient belongs to a treatment group are inferred.
There are no additional elements in the claim other than general purpose computer components. The general purpose computer components do not integrate and do not recite an inventive concept because they recite mere instructions to apply the exceptions. The mathematical calculations in the claim cannot be the basis for an improvement in technology. See MPEP 2106.05(f) (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”).
Applicant further argues
Step 2B Even assuming, arguendo, that claim 1 is directed to the alleged abstract idea, claim 1 recites meaningful unconventional elements that amount to significantly more than the alleged abstract idea.
Unconventional mathematical concepts, without significantly more, are not patent eligible. See MPEP 2106.05(f) (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”).
Applicant further argues
Applicant's claim 1, as presented 13
herein, include specific recitations directed to other than what is well-understood, routine, and conventional in the field.
For example, an inventive concept can be found in the non-conventional and non-generic arrangement of the features of the claims (e.g., the combination of features of the claims is non-conventional and non-generic). See BASCOM Global Internet Services, Inc., v. AT&T Mobility LLC, AT&T Corp., 827 F.3d 1341 (Fed. Cir.
2016); see also Ancora Techs. v. HTC Am., Inc., 908 F.3d 1343, 1346 (Fed. Cir.
2018) (determining that the claims at issue, relating to improving security against a computer's unauthorized use of a program, were directed to an improvement in computer functionality due to the claims having "the specificity required to transform [the] claim[s] from...claiming only a result to...claiming a way of achieving it" under Step 2A, but also acknowledging that such a technical improvement can establish eligibility under Step 2B in view of BASCOM). In BASCOM, the court indicated that, when looking at the claim as an ordered combination of claim limitations, "an inventive concept can be found in the non-conventional and non-generic arrangement of known, conventional pieces."
Unconventional mathematical concepts, without significantly more, are not patent eligible. See MPEP 2106.05(f) (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”). The additional elements in the claims do not reflect anything but conventional computer components. Applicant’s argument is therefore not persuasive.
Applicant argues
Similar to the concepts discussed in BASCOM, Applicant's claim 1 includes additional elements that are sufficient to ensure that the claims amount to significantly more than an abstract idea.
The additional elements in the claims do not reflect anything but conventional computer components. They are mere instructions to apply the exception and thus do not recite significantly more. See above and MPEP 2106.05(f). Applicant’s argument is therefore not persuasive.
Applicant argues
For example, Applicant's amended clam 1 recites:
a third calculation process of calculating a pointwise weight vector for each of the plurality of samples based on a third learning parameter and the reallocation vector calculated by the second calculation process, and execute a fourth calculation process of calculating, for each sample, a prediction value for an assignment variable to be assigned to the sample, based on the feature vector and the pointwise weight vector calculated by the third calculation process.
These elements explicitly recite “calculation” and, when these elements are read broadly in light of the specification, it is clear these calculations recite mathematical concepts. See e.g. Spec pp. 13-16 equations 1-4.
Applicant further argues
These elements are significant, at least because the claim includes a specific technique for improving the field of estimating efficacy of a medical therapy or a drug by improving how propensity scores (i.e., assignment variables) indicating a probability that a patient belongs to a treatment group are inferred.
There is no specific technique recited or reflected in the claims. Claim 1, for example, recites 4 mathematical concepts configured to be executed on a general purpose computer. Applicant’s argument is not persuasive.
Applicant argues
Accordingly, the sum of the functions of the additional elements of Applicant's claim 1, at least when viewed as an ordered combination, are significantly more than when each is taken alone.
The sum of the functions in the claims is explicitly a mathematical concept. Unconventional mathematical concepts, without significantly more, are not patent eligible. See MPEP 2106.05(f) (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”). The additional computer components in the claim are mere instructions to apply the exception and thus do not recite significantly more than the abstract idea. Lastly, that the calculations are performed on a general purpose computer do not necessarily make them patent eligible. See MPEP 2106.04(a)(2)(III)(C) (“A Claim That Requires a Computer May Still Recite a Mental Process”). Applicant’s argument is therefore not persuasive.
Applicant further argues
Therefore, similar to the claims in BASCOM, Applicant's claim 1, at least as an ordered combination, includes a non-conventional and non-generic arrangement of features comprising an inventive concept.
The ordered combination of elements recite four mathematical concepts being configured to be executed on a general purpose computer. The only unconventional elements of the claim are the mathematical concepts. Examiner submits executing unconventional mathematical concepts on a conventional computer is not patent eligible. The additional, conventional elements in the claim do not reflect the disclosed improvement and the abstract idea itself cannot reflect an improvement in technology even if the abstract idea is unconventional. There is nothing about the combination of these elements that cause the claim to be patent eligible.
Applicant further
As such, Applicant's claim 1 is not directed to routine, conventional, or well-known activities. Consequently, even if Applicant's claim 1 includes an abstract idea, the claim includes additional elements that singly and as an ordered combination amount to significantly more than the mere abstract idea, and therefore, Applicant's claim 1 is patent-eligible for these reasons as well.
Examiner agrees the abstract idea elements in claim 1, for example, do not recite well-understood, routine, and conventional calculations. Unfortunately, even unconventional abstract idea elements, without significantly more, are not patent eligible. See MPEP 2106.05. (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”). Here, the additional, conventional computer components simply do not reflect an improvement in technology. . See MPEP 2106.04(a)(2)(III)(C) (“A Claim That Requires a Computer May Still Recite a Mental Process”). Applicant’s argument is therefore not persuasive.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALBERT M PHILLIPS, III whose telephone number is (571)270-3256. The examiner can normally be reached 10a-6:30pm EST M-F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann J Lo can be reached at (571) 272-9767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALBERT M PHILLIPS, III/Primary Examiner, Art Unit 2159
1 See also MPEP 2106.05. (“. . it is important to keep in mind that an improvement in the abstract idea itself . . . is not an improvement in technology.”). See also Recentive Analytics, Inc., v. Fox Corp., Appeal No. 2023-2437 (Fed. Cir. Apr. 18, 2025)
Machine learning is a burgeoning and increasingly important field and may lead to patent-eligible improvements in technology. Today, we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.