DETAILED ACTION
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 . This application is in response to the set of claims received on June 27, 2025. Claims 1-20 are currently pending.
Claim Objections
Claim 2 is objected to because of the following informalities: Claim 2, line 3 “model, parameters” should read –model parameters--. Appropriate correction is required.
Claim 3 is objected to because of the following informalities: Claim 3, line 4 “control, based” should read –control based--. Appropriate correction is required.
Claim 6 is objected to because of the following informalities: Claim 6, line 4 “determine, based on the at least one image, at least one constraint” should read – determine based on the at least one image at least one constraint--. Appropriate correction is required.
Claim 10 is objected to because of the following informalities: Claim 10, line 3 “input to the model, parameters” should read – input to the model, parameters--. Appropriate correction is required.
Claim 11 is objected to because of the following informalities: Claim 11, line 4 “control, a robot” should read –control a robot--. Appropriate correction is required.
Claim 14 is objected to because of the following informalities: Claim 14, line 4 “determine, based on the at least one image, at least one constraint” should read – determine based on the at least one image at least one constraint--. Appropriate correction is required.
Claim 17 is objected to because of the following informalities: Claim 17, line 4 “receive, from an imaging device, at least one constraint” should read – receive, from an imaging device, at least one constraint--. Claim 17, line 6 ““determine, based on the at least one image, at least one constraint” should read – determine based on the at least one image at least one constraint--. Appropriate correction is required. Claim 17, line 10, “select, based on the scores generated by the model, an implant plan option” should read –select based on the scores generated by the model an implant plan option--. Appropriate correction is required.
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 1,2,4-7,9,10, and 12-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. The claims recite at least one step or instruction for automatically training and using an implant plan evaluation model. This judicial exception is not integrated into a practical application because it’s considered a mental process, i.e., concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP 2106.04(a)(2)(III))]]. The claims do include additional elements that are sufficient to amount to significantly more than the judicial exception (see the detailed explanation below.
In accordance with MPEP 2106.04, each of Claims 1,2,4-7,9,10, and 12-15 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1 per MPEP 2106.04(a)
Each of Claims 1,2,4-7,9,10, and 12-15 recites at least one step or instruction for automatically training and using an implant plan evaluation model, which is grouped as a mental process in MPEP 2106.04(a)(2)(III) or a certain method of organizing human activity in MPEP 2106.04(a)(2)(II), i.e., a Mental process or concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP 2106.04(a)(2)(III))]].
Accordingly, each of Claims 1,2,4-7,9,10, and 12-15 recites an abstract idea.
Specifically, claim 1 recites a system for training a model, comprising
a user interface (additional element);
a processor (additional element); and
a memory storing instructions for execution by the processor (additional element) that, when executed, cause the processor to receive a first implant plan option having a first set of parameters and a second implant plan option having a second set of parameters (observation or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III))
; input the first set of parameters and the second set of parameters into a model configured to score the first implant plan option based on the first set of parameters and the second implant plan option based on the second set of parameters (judgment or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III))
;compare the score of the first implant plan option and the score of the second implant plan option(judgment or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III));and when the score of the second implant plan option is higher than the score of the first implant plan option, adjust the model to score the first implant plan option higher than the second implant plan option(observation or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III)).
Specifically, claim 9 recites a system, comprising:
a processor(additional element); and a memory storing instructions for execution by the processor(additional element) that, when executed, cause the processor to: receive a first implant plan option having a first set of parameters and a second implant plan option having a second set of parameters; (observation or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III)); input the first set of parameters and the second set of parameters into a model configured to score the first implant plan option based on the first set of parameters and the second implant plan option based on the second set of parameters; (judgment or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III)); compare the score of the first implant plan option and the score of the second implant plan option; (judgment or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III)); and when the score of the second implant plan option is higher than the score of the first implant plan option, adjust the model to score the first implant plan option higher than the second implant plan option; (observation or evaluation, which is grouped as a mental process in MPEP 2106.04(a)(2)(III)).
Further, dependent Claims 2,4-7,10,and 12-15 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea as in MPEP 2106.04(a).
Step 2A, Prong 2 per MPEP 2106.04(d)
The above-identified abstract idea in each of independent Claims 1 and 9 (and their respective dependent Claims 2,4-7,10,12-15) is not integrated into a practical application under MPEP 2106.04(d) because the additional elements (identified above in independent Claims 1-9), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use according to MPEP 2106.05(h). More specifically, the additional elements of: a user interface, a processor, and a memory as recited in independent Claim 1 and its dependent claims; and a processor and memory as recited in independent Claim 9 and its dependent claims are generically recited computer elements in independent Claims 1 and 9 (and their respective dependent claims) which do not improve the functioning of a computer, or any other technology or technical field according to MPEP 2106.04(d)(1) and 2106.05(a). Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine according to MPEP 2106.05(b), effect a transformation according to MPEP 2106.05(c), provide a particular treatment or prophylaxis according to MPEP 2106.04(d)(2) or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception according to MPEP 2106.04(d)(2) and 2106.05(e). Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer in accordance with MPEP 2106.05(f). For at least these reasons, the abstract idea identified above in independent Claims 1 and 9 (and their respective dependent claims) is not integrated into a practical application in accordance with MPEP 2106.04(d).
Moreover, the above-identified abstract idea is not integrated into a practical application in accordance with MPEP 2106.04(d) because the claimed method and system merely implement the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer (e.g., user interface, processor, and memory as claimed). In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer according to MPEP 2106.05(f). Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims according to MPEP 2106.05(a). That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claims 1 and 9 (and their respective dependent claims) is not integrated into a practical application under MPEP 2106.04(d)(I).
Accordingly, independent Claims 1 and 9 (and their respective dependent claims) are each directed to an abstract idea according to MPEP 2106.04(d).
Step 2B per MPEP 2106.05
None of Claims 1,2,4-7,9,10, and 12-15 include additional elements that are sufficient to amount to significantly more than the abstract idea in accordance with MPEP 2106.05 for at least the following reasons.
These claims require the additional elements of a user interface, a processor, and a memory as recited in independent Claim 1 and its dependent claims; and a processor and memory as recited in independent Claim 9 and its dependent claims.
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, MPEP 2106.05(d)(II) along with Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. [[Only use this paragraph if one or more claims is directed to a mental process. If no claim is directed to a mental process, delete this paragraph.
Per Applicant’s specification,
In one or more examples, the described methods, processes, and techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer) [0042].
Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i9 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple A11, A12, A12X, A12Z, or A13 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radcon RX 6000-scrics processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term "processor" as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements [0043]
The memory 106 may be or comprise RAM, DRAM, SDRAM, other solid-state memory, any memory described herein, or any other tangible, non-transitory memory for storing computer- readable data and/or instructions. The memory 106 may store information or data useful for completing, for example, any step of the methods 200 and/or 300 described herein, or of any other methods. The memory 106 may store, for example, one or more image processing algorithms 120, one or more training algorithms 122, and/or instructions 124. Such instructions or algorithms may, in some embodiments, be organized into one or more applications, modules, packages, layers, or engines. The algorithms and/or instructions may cause the processor 104 to manipulate data stored in the memory 106 and/or received from or via the imaging device 112, the robot 114, the database 130, and/or the cloud 134 [0054].
The computing device 102 may also comprise one or more user interfaces 110. The user interface 110 may be or comprise a keyboard, mouse, trackball, monitor, television, screen, touchscreen, and/or any other device for receiving information from a user and/or for providing information to a user. The user interface 110 may be used, for example, to receive a user selection or other user input regarding any step of any method described herein. Notwithstanding the foregoing, any required input for any step of any method described herein may be generated automatically by the system 100 (e.g., by the processor 104 or another component of the system 100) or received by the system 100 from a source external to the system 100. In some embodiments, the user interface 110 may be useful to allow a surgeon or other user to modify instructions to be executed by the processor 104 according to one or more embodiments of the present disclosure, and/or to modify or adjust a setting of other information displayed on the user interface 110 or corresponding thereto [paragraph 0056].
Accordingly, in light of Applicant’s specification, the claimed terms user interface, processor and memory are reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process. See MPEP 2106.05(f).
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the user interface, processor and memory. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements 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) (see MPEP 2106.05(d)(I)(2) and 2106.07(a)(III)). Adding hardware that performs “‘well understood, routine, conventional activities’ previously known to the industry” will not make claims patent-eligible (TLI Communications along with MPEP 2106.05(d)(I)).
The recitation of the above-identified additional limitations in Claims 1,2,4-7,9,10, and 12-15 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See MPEP 2106.05(f) along with Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. See MPEP 2106.05(a) along with McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, per MPEP 2106.05(a), the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the system for training a model of Claims 1,2,4-7,9,10, and 12-15 are directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself or providing a technical solution to a problem in a technical field according to MPEP 2106.05(a), or (ii) providing meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself according to MPEP 2106.04(d)(2) and 2106.05(e).
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claims 1 and 9 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment according to MPEP 2106.05(h). When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment according to MPEP 2106.05(h). When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself according to MPEP 2106.04(d)(2) and 2106.05(e). Moreover, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity according to MPEP 2106.05(g). As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application as required by MPEP 2106.05.
Therefore, for at least the above reasons, none of the Claims 1,2,4-7,9,10, and 12-15amounts to significantly more than the abstract idea itself. Accordingly, claims 1,2,4-7,9,10, and 12-15 are not patent eligible and rejected under 35 U.S.C. 101.
It is recommended to incorporate sufficient structure that performs the output, i.e., a robot to perform the surgical step (claims 3 and 11) or yields a tangible result, i.e., placement options for a spinal implant (claims 8 and 16).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 2, 4, 5, 7-10, 12, 13, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Anderson et al. (US Publication 2010/0191100) in view of Naver (EP 3920100 A1).
Regarding claim 1, Anderson discloses a system (10, Figure 1) for training a model (i.e., a computer-implemented system for evaluating patient-specific treatment and implant plans [0128]), comprising: a user interface [0128] ;a processor (i.e., computer processor [0128])); and a memory (block 284 [0128]) storing instructions for execution by the processor that, when executed, cause the processor to: receive a first implant plan option having a first set of parameters and a second implant plan option having a second set of parameters (i.e., block 286 performs simulations of treatment alternatives, the physician can repeatedly evaluate different treatment scenarios and then select the treatment at block 288. The selected treatment is used to choose implants at block 290); input the first set of parameters and the second set of parameters into a model configured to score the first implant plan option based on the first set of parameters and the second implant plan option based on the second set of parameters; compare the score of the first implant plan option and the score of the second implant plan option (i.e., generate comparative evaluations/rankings from which a preferred treatment plan is selected [0128]); and when the score of the second implant plan option is higher than the score of the first implant plan option (i.e., there’s subsequent modeling and expressly considers physician preferences and previous successful treatment information in determining appropriate treatments [0128],
Anderson fails to disclose adjusting the model to score the first implant plan option higher than the second implant plan option.
Naver, however, teaches machine-learning technique (i.e., a learnable scoring function that receives items and generate respective scores (see Figures 1-2, particularly training step 102. The training data includes pairs of items that have a known relative preference and relevance. The scoring function f generates respective scores i and j, and the resulting ranking is compared with the known preference (see Figure 2, and the pairwise probability loss discussion.
Therefore, it would have been obvious to a person having ordinary skill in the art at the time the invention was made to modify the treatment-plan evaluation and modeling system of Anderson with a learning and rankings technique model of Naver so that when the model-generated ranking differs from the known physician preference between two treatment implant plans, the learning parameters are adjusted so the model ranks the known preferred plan above the other plan.
Regarding claim 2, the modified Anderson’s system discloses wherein the memory stores additional instructions for execution by the processor that, when executed, further cause the processor to: input to the model, parameters corresponding to each implant plan option of a set of implant plan options to yield a score for each implant plan option; select the implant plan option from the set of implant plan options with the highest score; and display the selected implant plan option on the user interface (i.e., Anderson teaches evaluating a plurality of treatment alternatives, ranking the alternatives based upon modeled/simulated results, and selecting the treatment determined to best satisfy the applicable treatment considerations. see Figure 18, steps 286-290, [paragraphs 0128-0131]).
Regarding claim 4, the modified Anderson’s system discloses wherein the memory stores additional instructions for execution by the processor that, when executed, further cause the processor to: prompt a user to accept the selected implant plan option (i.e., Anderson discloses a physician interacting with a computer-generated treatment alternative and selecting the desired treatment [paragraphs 0128-0131]).
Regarding claim 5, the modified Anderson’s system discloses wherein at least one of the first set of parameters and the second set of parameters comprises a surgical parameter or a safety parameter (i.e., Anderson discloses evaluating treatment plans based upon treatment and implant parameters and patient characteristics, including parameters relating to implant selection and positioning [paragraphs 0128-0131]).
Regarding claim 7, the modified Anderson’s system discloses adjusting the model to score the first implant plan option higher than the second implant plan option comprises determining a weight for at least one parameter of the first set of parameters and the second set of parameters (i.e., Anderson discloses applying weighted factors to treatment alternatives and desired outcomes in evaluating the treatment plans, see Figures 18, step 286 and the weighted treatment factors).
Regarding claim 8, the modified Anderson’s system discloses each of the first implant plan option and the second implant plan option corresponds to placement options for a spinal implant (i.e., Anderson discloses treatment planning to spinal treatment and spinal implants, including selection of spinal implants and implant parameters [0018]).
Regarding claim 9, Anderson discloses a system, comprising: a processor (i.e., computer processor [0128])); and a memory storing instructions( block 284 [0128]) for execution by the processor that, when executed, cause the processor to: receive a first implant plan option having a first set of parameters and a second implant plan option having a second set of parameters (i.e., block 286 performs simulations of treatment alternatives, the physician can repeatedly evaluate different treatment scenarios and then select the treatment at block 288. The selected treatment is used to choose implants at block 290); input the first set of parameters and the second set of parameters into a model configured to score the first implant plan option based on the first set of parameters and the second implant plan option based on the second set of parameters); input the first set of parameters and the second set of parameters into a model configured to score the first implant plan option based on the first set of parameters and the second implant plan option based on the second set of parameters [paragraphs 0128-0131]; compare the score of the first implant plan option and the score of the second implant plan option; and when the score of the second implant plan option is higher than the score of the first implant plan option (i.e., there’s subsequent modeling and expressly considers physician preferences and previous successful treatment information in determining appropriate treatments [0128].
Anderson fails to disclose adjusting the model to score the first implant plan option higher than the second implant plan option.
Naver, however, teaches machine-learning technique (i.e., a learnable scoring function that receives items and generate respective scores (see Figures 1-2, particularly training step 102. The training data includes pairs of items that have a known relative preference and relevance. The scoring function generates respective scores i and j, and the resulting ranking is compared with the known preference (see Figure 2, and the pairwise probability loss discussion.
Therefore, it would have been obvious to a person having ordinary skill in the art at the time the invention was made to modify the treatment-plan evaluation and modeling system of Anderson with a learning and rankings technique model of Naver so that when the model-generated ranking differs from the known physician preference between two treatment implant plans, the learning parameters are adjusted so the model ranks the known preferred plan above the other plan.
Regarding claim 10, the modified Anderson’s system discloses wherein the memory stores additional instructions for execution by the processor that, when executed, further cause the processor to: input to the model, parameters corresponding to each implant plan option of a set of implant plan options to yield a score for each implant plan option; select the implant plan option from the set of implant plan options with the highest score; and display the selected implant plan option on the user interface(i.e., Anderson teaches evaluating a plurality of treatment alternatives, ranking the alternatives based upon modeled/simulated results, and selecting the treatment determined to best satisfy the applicable treatment considerations. see Figure 18, steps 286-290, [paragraphs 0128-0131]).
Regarding claim 12, the modified Anderson’s system discloses wherein the memory stores additional instructions for execution by the processor that, when executed, further causes the processor to: prompt a user to accept the selected implant plan option (i.e., Anderson discloses a physician interacting with a computer-generated treatment alternative and selecting the desired treatment [paragraphs 0128-0131]).
Regarding claim 13, the modified Anderson’s system discloses at least one of the first set of parameters and the second set of parameters comprises a surgical parameter or a safety parameter (i.e., Anderson discloses evaluating treatment plans based upon treatment and implant parameters and patient characteristics, including parameters relating to implant selection and positioning [paragraphs 0128-0131]).
Regarding claim 15, the modified Anderson’s system discloses wherein adjusting the model to score the first implant plan option higher than the second implant plan option comprises determining a weight for at least one parameter of the first set of parameters and the second set of parameters(i.e., Anderson discloses applying weighted factors to treatment alternatives and desired outcomes in evaluating the treatment plans, see Figures 18, step 286 and the weighted treatment factors).
Regarding claim 16, the modified Anderson’s system wherein each of the first implant plan option and the second implant plan option corresponds to placement options for a spinal implant (i.e., Anderson discloses treatment planning to spinal treatment and spinal implants, including selection of spinal implants and implant parameters [0018]).
Claims 3 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Anderson et al. (US Publication 2010/0191100) and Naver (EP 3920100 A1), further in view of de Souza et al. (US Publication 2020/0188026), hereafter “de Souza).
Regarding claim 3, the modified Anderson’s system fails to disclose wherein the memory stores additional instructions for execution by the processor that, when executed, further cause the processor to: generate a surgical step for a surgical plan based on the selected implant plan option; and control, based on the selected implant plan option, a robot to perform the surgical step.
De Souza, however, teaches a processor to: generate a surgical step for a surgical plan based on the selected implant plan option; and control, based on the selected implant plan option, a robot (60, Figure 1) to perform the surgical step (i.e., as shown in Figure 2: computer (50, Figure 1) develops the surgical plan; the plan determines implant positioning and required resections/drill holes.
Therefore, it would have been obvious to a person having a person of ordinary skill in the art at the time the invention was made to modify the modified Anderson’s system with a surgical step of using a robot to perform the surgical step as taught de Souza to perform the bone resections.
Regarding claim 11, the modified Anderson’s system discloses wherein the memory stores additional instructions for execution by the processor that, when executed, further cause the processor (50, Figure 1) to: generate a surgical step for a surgical plan based on the selected implant plan option; and control, a robot (60, Figure 1) to perform the surgical step i.e., as shown in Figure 2: computer (50) develops the surgical plan; the plan determines implant positioning and required resections/drill holes).
Allowable Subject Matter
Claims 6 and 14 are objected to as being dependent upon a rejected base claim but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 17-20 are allowed.
Reasons for Allowance
The following is an examiner’s statement of reasons for allowance: The prior art of record, alone or in combination, fails to teach or suggest automatically generate a set of implant plan options based on the at least one constraint. The cited prior art neither discloses nor renders obvious this feature, and there is no teaching, suggestion, or motivation that would have led one of ordinary skill in the art to modify or combine the references to arrive at the claimed invention. Accordingly, the claims are considered allowable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DIANA S JONES whose telephone number is (571)270-5963. The examiner can normally be reached Monday to Friday (8am to 4pm EST).
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, Kevin Truong can be reached at 571-272-4705. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Diana Jones/Examiner, Art Unit 3775
/Zade Coley/Primary Examiner, Art Unit 3775
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