DETAILED ACTION
Notice to Applicant
This communication is in response to the amendment submitted May 11, 2026. Claims 11 – 13 and 19 are amended. Claims 11 – 22 are pending.
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 Objections
The objection to Claim 12 is withdrawn based upon the amendment submitted May 11, 2026.
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 11 – 22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step One
Claims 11 –22 are drawn to a method, which is/are statutory categories of invention (Step 1: YES).
Step 2A Prong One
Independent claim 11 recites providing intravenous nutrients to a premature baby including obtaining an electronic health record of the premature baby, selecting a nutrient bag comprising a mix of nutrients to supplement the health of the individual based on a recommendation, deriving a plurality of sequences of concept codes based on the time ordered health records of the mother and baby, and providing the selected nutrient bag to the baby.
Independent claim 19 recited obtaining health information about an individua wherein the health information comprises health records comprising a time-ordered sequence of concept codes that include details about the individual's health, and the individual is a premature baby, deriving a plurality of sequences of concept codes based on the time ordered health records of the mother and baby, and providing a dietary recommendation for the individual.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity, as reflected in the specification, which relates to identifying neonatal risk, especially in preterm births (paragraph 3). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because they address providing a nutrient bag including a mix of nutrients to supplement the health of the preterm infant (paragraph 18). Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).”
Step 2A Prong Two
This judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including:
Claim 11: “electronic”, “multitask machine learning model”, “trained by a process comprising: constructing a code-code co-occurrence matrix based on a frequency with which concept codes co-occur within the plurality of time-ordered EHRs; training a Global Vectors (GloVe) model, using the code-code co-occurrence matrix, to generate vector embeddings for concept codes; generating, using the trained GloVe model, a vector embedding for each of the concept codes; converting each of the plurality of sequences of concept codes into a matrix by embedding each concept code in the sequence with its corresponding vector embedding; and training the multitask machine learning model, using the matrices for the plurality of sequences of concept codes, to predict neonatal health outcomes based upon embeddings derived from time-ordered sequences of concept codes”
Claim 12: “multitask machine learning model comprises an encoder, a hidden state, and a decoder, wherein the encoder reads an input, wherein the hidden state represents an internal learned representation of the input, and wherein the decoder interprets the interprets internal learned representation and reconstructs the input”
Claim 13: “bottleneck layer”
Claim 19: “electronic”, “multitask machine learning model”, “trained”, “constructing a code-code co-occurrence matrix based on a frequency with which concept codes co-occur within the plurality of time-ordered EHRs; training a Global Vectors (GloVe) model, using the code-code co-occurrence matrix, to generate vector embeddings for concept codes; generating, using the trained GloVe model, a vector embedding for each of the concept codes; converting each of the plurality of sequences of concept codes into a matrix by embedding each concept code in the sequence with its corresponding vector embedding; and training the multitask machine learning model, using the matrices for the plurality of sequences of concept codes, to predict neonatal health outcomes based upon embeddings derived from time-ordered sequences of concept codes”
Claim 22: “database”
These features are additional elements that are recited at a high level of generality such that they amount to no more than mere instruction to apply the exception using generic computer components. See: MPEP 2106.05(f).
The additional elements are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
The combination of these additional elements is no more than mere instructions to apply the exception using generic computer components. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic components cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are not integrated into the claim because they are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See: MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The specification, as filed, supports this conclusion as follows:
[0070] Artificial neural networks (NNs) are a family of computing systems based on a collection of connected units or nodes, which receive a signal (input data or the signal returned by previous units), process it and then transmit it to the following units. Units are aggregated into layers, and each layer may perform different transformations on their inputs. Signals travel from the first layers (the input layers), to the last layers (the output layers containing the object of the prediction). Many embodiments use NNs due their ability to process vast amount of data, to learn and model complex non-linear relationships that can be generalized to unseen data, and because NNs do not require strict assumptions regarding the distribution of input variables and their associations. In the presence of multiple outcomes, multi-task learning allows prediction of multiple outcomes at the same time by leveraging representations that are shared across related outcomes. Additionally, recurrent NNs (RNNs) use their internal state (e.g., memory), taking information from prior inputs to influence the current input and output Unlike traditional NNs, where inputs and outputs are independent of each other, the output of recurrent NNs depends on the prior elements within the sequence. long Short-Term Memory (LSTM) are a particular type of RNN, proposed to address the problem of long term dependencies, e,g., when the previous state that is influencing the current prediction is not in the recent past, but in a more distant past.
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with routine, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claim(s) 12 – 18 and 20 – 22 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea without significantly more. These claims fail to remedy the deficiencies of their parent claims above, and are therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
Claim Rejections - 35 USC § 103
The rejection of Claim(s) 11 is/are under 35 U.S.C. 103 as being unpatentable over Neumann (U.S. Patent Number 11,935,642 B2) in view of Jacob et al., herein after Jacob (U.S. Publication Number 2013/0191150 A1) is withdrawn based upon the amendment submitted May 11, 2026.
The rejection of Claim(s) 12 – 13 and 16 – 18 under 35 U.S.C. 103 as being unpatentable over Neumann (U.S. Patent Number 11,935,642 B2) in view of Jacob et al., herein after Jacob (U.S. Publication Number 2013/0191150 A1) further in view of Hsu et al., herein after Hsu (U.S. Publication Number 2021/0158967 A1) is withdrawn based upon the amendment submitted May 11, 2026.
The rejection of Claim(s) 14 under 35 U.S.C. 103 as being unpatentable over Neumann (U.S. Patent Number 11,935,642 B2) in view of Jacob et al., herein after Jacob (U.S. Publication Number 2013/0191150 A1) further in view of Hsu et al., herein after Hsu (U.S. Publication Number 2021/0158967 A1) in view of Hoath et al., herein after Hoath (U.S. Patent Number 6,333,041 B1) is withdrawn based upon the amendment submitted May 11, 2026.
The rejection of Claim(s) 15 under 35 U.S.C. 103 as being unpatentable over Neumann (U.S. Patent Number 11,935,642 B2) in view of Jacob et al., herein after Jacob (U.S. Publication Number 2013/0191150 A1) further in view of Hsu et al., herein after Hsu (U.S. Publication Number 2021/0158967 A1) in view of Lambers et al., herein after Lambers (U.S. Publication Number 2018/0332881 A1) is withdrawn based upon the amendment submitted May 11, 2026.
Claim Rejections - 35 USC § 102
The rejection of Claim(s) 19 – 22 under 35 U.S.C. 102(a)(1) as being anticipated by Neumann (U.S. Patent Number 11,935,642 B2) is withdrawn based upon the amendment submitted May 11, 2026.
Response to Arguments
Applicant's arguments filed May 11, 2026 have been fully considered but they are not persuasive. The Applicant’s arguments have been addressed in the order in which they were presented.
Claim Rejections - 35 USC § 101
The Applicant argues the present claims, as amend do not recite a judicial exception, citing Example 39 of the USPTO Subject Matter Eligibility examples. The Examiner respectfully disagrees. Example 39 recites “A computer-implemented method of training a neural network for facial detection comprising: collecting a set of digital facial images from a database; applying one or more transformations to each digital facial image including mirroring, rotating, smoothing, or contrast reduction to create a modified set of digital facial images; creating a first training set comprising the collected set of digital facial images, the modified set of digital facial images, and a set of digital non-facial images; training the neural network in a first stage using the first training set; creating a second training set for a second stage of training comprising the first training set and digital non-facial images that are incorrectly detected as facial images after the first stage of training; and training the neural network in a second stage using the second training set”, nothing in the claim precludes the step from practically being performed in the mind. The additional elements of Example 39 recite a specific manner of performing an iterative training algorithm, in which the system is retrained with an updated training set containing false positives introduced after face detection was performed on a set of non-facial images. The present claims differ such that the additional elements include “electronic”, “multitask machine learning model”, “trained by a process comprising: constructing a code-code co-occurrence matrix based on a frequency with which concept codes co-occur within the plurality of time-ordered EHRs; training a Global Vectors (GloVe) model, using the code-code co-occurrence matrix, to generate vector embeddings for concept codes; generating, using the trained GloVe model, a vector embedding for each of the concept codes; converting each of the plurality of sequences of concept codes into a matrix by embedding each concept code in the sequence with its corresponding vector embedding; and training the multitask machine learning model, using the matrices for the plurality of sequences of concept codes, to predict neonatal health outcomes based upon embeddings derived from time-ordered sequences of concept codes”. The claim, as a whole, merely describes how to generally “apply” the concept of receiving or obtaining a time-ordered sequence of codes from a patients medical record, both maternal and newborn, using a model (as described in the Applicant’s specification). The claimed computer components are recited at a high level of generality and are merely invoked as tools to perform an existing medical records update process. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the Applicant’s argument is not persuasive and the rejection is maintained.
The Applicant argues the amended claims integrate any judicial exception into a practical application, and is therefore not directed to a judicial exception. The Examiner respectfully disagrees. The additional elements of the present claims fail to integrate the exception into a practical application of the exception. The 2019 PEG defines the phrase “integration into a practical application” to require an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception. For example, the 2019 PEG guidelines recite limitations that are indicative of integration into a practical application when recited in a claim with a judicial exception include:
Improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e) and the Vanda Memo issued in June 2018.
The Applicant argues the amended claims recite non-conventional and non-generic arrangement of known, conventional pieces, citing Berkheimer. The Berkheimer memo discloses “a citation to an express statement in the specification or to a statement made by applicant during prosecution that demonstrates the well-understood, routine, conventional nature of additional elements.” The Examiner submits the Berkheimer memo requires factual support on the record, which is shown in the 101 rejection above, as well as in the response to the Applicant’s 101 argument. The Applicant’s published specification supports the elements in the claims are “well-understood, routine, and conventional”. The Berkheimer memo recites “In a step 2B analysis, an additional element (or combination of elements) is not well-understood, routine or conventional unless the examiner finds, and expressly supports a rejection in writing with, one or more of the following: 1. A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s). A specification demonstrates the well-understood, routine, conventional nature of additional elements when it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a). A finding that an element is well-understood, routine, or conventional cannot be based only on the fact that the specification is silent with respect to describing such element.” The Examiner has cited multiple paragraphs in the Applicant’s as filed specification (see above) which are directed to well-understood, routine or conventional elements. Thus, the Applicant’s argument is not persuasive and the rejection is maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRISTINE K RAPILLO whose telephone number is (571)270-3325. The examiner can normally be reached Monday - Friday 7:30 - 4 pm.
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/K.K.R/Examiner, Art Unit 3682 /ROBERT A SOREY/Primary Examiner, Art Unit 3682
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