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 .
Status Of Claims
This action is in reply to the application filed on 02/26/2024.
Claims 1-20 are currently pending and have been examined.
Excessive IDS
The Applicant has submitted over 500 references consisting of over 3700 pages. In order for the Examiner to properly determine patentability over prior art submitted, it is requested that the Applicant explain the significance of each reference or highlight those documents which have been specifically brought to Applicant’s attention and/or are known to be of most significance. Specifically, the Applicant is requested to point out to the Examiner which references teach providing customizable insurance according to consumer preferences and attributes.
It is desirable to avoid the submission of long list of documents. The Examiner hereby requests elimination of clearly irrelevant and marginally pertinent cumulative information. See Penn Yan Boats, Inc. v. Sea Lark Boats, Inc. 359 F. Supp. 948, 175 USPQ 260 (S.D.Fla.1972), aff’d, 479 F.2d 1338, 178 USPQ 577 (5th Cir. 1973), cert. Denied, 414 U.S. 874 (1974). But cf. Molins PLC v. Textron, Inc., 48 F.3d 1172, 33 USPQ2d 1823 (Fed. Cir. 1995).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11,915,816 in view of McNutt et al., US Patent No. 11,495,355.
Each of the limitations included in claims 1-20 of the instant application are also recited in claims 1-20 of the ‘816 patent. However, claims 1-20 of the instant application recite one of more machine learning models in place of the artificial intelligence engine configured to use one or more machine learning models recited in claims 1-20 of the ‘816 patent. Because claims 1-20 of the ‘816 patent recite the same functions being carried out, this difference does not patentably distinguish the claims. McNutt et al. teaches creating multiple machine learning models and using them to improve outcome and care management individualized to the patient (see (227), we created five machine learning models each for two complications); (238), One goal is for generalizable risk prediction models with machine learning algorithms and use the variable features that most impact a particular … outcome for stratified groups of patients. The objective is to develop data science models that maximize the significance of prediction. Finally, we will ascertain the clinical utility for treatment plan quality assessment and care management individualized to the patient). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to add the various machine learning models recitations to claims 1-20 of the ‘816 patent with the motivation of further addressing the need to using machine learning to generate treatment plans to optimize patient outcome (see (78) and (243) of McNutt et al.).
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-20: Step 1
Claims 1-10 are drawn to a method for generating patient treatment plans using machine learning model(s), which is within the four statutory categories (i.e. process). Claims 11-19 are drawn to a system for generating patient treatment plans using machine learning model(s), which is within the four statutory categories (i.e. apparatus). Claim 20 is drawn to a tangible non-transitory computer-readable medium storing instructions that when executed cause a processing device to generate patient treatment plans using machine learning model(s), which is within the four statutory categories (i.e. apparatus).
Claims 1-20: Step 2A Prong One
Claim 1 recites receiving attribute data associated with a user, while the user uses an electromechanical machine to perform a first treatment plan for the user, receiving measurement data associated with the user, generating, a second treatment plan for the user, wherein the generating is based on at least the attribute data associated with the user and the measurement data associated with the user, and wherein the second treatment plan comprises a description of one or more predicted disease states of the user. Claims 11 and 20 recite similar limitations.
These limitations, as drafted, given the broadest reasonable interpretation, but for the recitation of generic computer components, encompass managing personal behavior by manually following rules or instructions, which is a subgrouping of Certain Methods of Organizing Human Activity. But for the recitation of generic computer components, these limitations encompass a user receiving attribute data associated with a user, while the user uses an electromechanical machine to perform a first treatment plan for the user, receiving measurement data associated with the user, generating a second treatment plan for the user, wherein the generating is based on at least the attribute data associated with the user and the measurement data associated with the user, and wherein the second treatment plan comprises a description of one or more predicted disease states of the user. These steps could be carried out manually by a user following rules or instructions, which is a subgrouping of Certain Methods of Organizing Human Activity. Claims 11 and 20 recite similar limitations.
Claims 2-10 and 12-19 incorporate the abstract idea identified above and recite additional limitations that expand on the abstract idea, but for the recitation of generic computer components. For example, but for the recitation of generic computer components, Claims 2 and 12 further define determining associations between confirmed disease states of the user and generating training data and updated model. Claims 3 and 13 further define generating third treatment plan. Claims 4 and 14 further define generating a set of questions concerning symptoms of the user. Claims 5 and 15 further define generating a set of additional questions concerning symptoms of the user. Claims 6 and 16 further define each of the predicted disease state(s) has a corresponding probability score. Claims 7 and 17 further define sending signals and adjusting portions. Claims 8 and 18 further define clinical portal. Claims 9 and 19 further define user portal. Claim 10 further defines the second treatment plan. Therefore, these claims are similarly drawn to Certain Methods of Organizing Human Activity.
Claims 1-20: Step 2A Prong Two
This judicial exception is not integrated into a practical application because the remaining elements amount to no more than general purpose computer components programmed to perform the abstract ideas along with insignificant, extra-solution data gathering activity, and adding limitations similar to adding the words “apply it” to the abstract idea. Claim 1 recites the additional elements that the treatment plan is generated by one or more machine learning models, and transmitting the treatment plan to a computing device. Claim 11 recites the additional elements of a memory device for storing instructions, processing device configured to execute the stored instructions, the treatment plan is generated by one or more machine learning models, and transmitting the treatment plan to a computing device. Claim 20 recites additional elements of a tangible, non-transitory computer-readable medium storing instructions that when executed causes a processing device to perform the steps, the treatment plan is generated by one or more machine learning models, and transmitting the treatment plan to a computing device.
Claims 1-20, directly or indirectly, recite the following generic computer components: “one or more machine learning models,” which are similar to adding the words “apply it” to the abstract idea. The written description discloses that the recited computer components encompass generic components including “The server 104 may include a training engine 118 capable of generating the one or more machine learning models 116. The training engine 118 may be a rackmount server, a router computer, a personal computer, a portable digital assistant, a smartphone, a laptop computer, a tablet computer, a netbook, a desktop computer, an Internet of Things (IoT) device, any other desired computing device, or any combination of the above“ (see at least Paragraph [0036]), and “The processing device 402 represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like” (see at least Paragraph [0052]). Although the additional element “machine learning model” limits the identified judicial exceptions, this type of limitation merely confines the use of the abstract idea to a particular technological environment (machine learning), and thus fails to add an inventive concept to the claims. See MPEP 2106.05 (h). As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
Claims 1-20: Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration into a practical application, the additional elements are recited at a high level of generality, and the written description indicates that these elements are generic computer components. Using generic computer components to perform abstract ideas does not provide a necessary inventive concept. See Alice, 573 U.S. at 223 (“mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). As explained above, the generic computer components and machine learning recited at a high level of generality are at best the equivalent of merely adding the words “apply it” to the judicial exception.
Receiving and transmitting data over a network (i.e. receiving and communicating data or signals) from various devices (i.e., electromechanical machine) has been recognized as well-understood, routine, and conventional activity of a general-purpose computer (see MPEP 2106.05(d) and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)).
Gathering and analyzing information using conventional techniques and displaying the result has also been found to be insufficient to show an improvement to technology, (see MPEP 2106.05(a) and TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48).
Insignificant, extra solution, data gathering activity has been found to not amount to significantly more than an abstract idea (see MPEP 2106.05(g) and Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)). Therefore, the high-level recitation of an output of results also fails to include additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, whether considered alone or in combination, the additional elements do not amount to significantly more than the abstract idea.
The most remarkable prior art of record is as follows:
Purdie: U.S. Patent U.S. 10,475,537 B2, Method And System For Automated Quality Assurance And Automated Treatment Planning Radiation Therapy
McNutt: U.S. Patent U.S. 11,495,355 B2, Method, System And Computer-Readable Media For Treatment Plan Risk Analysis
Kutzko: U.S. Patent U.S. 10,991,463 B2, Computer-Implemented System And Methods For Predicting The Health And Therapeutic Behavior Of Individuals Using Artificial Intelligence, Smart Contracts And Blockchain
McNair: U.S. Patent U.S. 11,527,326 B2, Dynamically Determining Risk Of Clinical Condition
Van Der Koijk: U.S. Patent Application Publication U.S. 2018/0052962 A1, Adaptive Treatment Management System With A Workflow Management Engine
Beene et al., “AI and Care Delivery: Emerging Opportunities For Artificial Intelligence To Transform How Care Is Delivered,” Nov 2019, American Hospital Association, pp. 1-12
Jeong et al.: “Computer-assisted upper extremity training using interactive biking exercise (iBikE) platform,” September 2012, pp. 1-5, 34th Annual International Conference of the IEEE EMBS
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Joy Chng whose telephone number is 571.270.7897. The examiner can normally be reached on Monday-Friday, 9:00am-5:00pm.
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/Joy Chng/
Primary Examiner, Art Unit 3686
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