Prosecution Insights
Last updated: July 17, 2026
Application No. 18/275,571

SAMPLE COLLECTION CALL TIME PREDICTION SYSTEM AND METHOD

Non-Final OA §101
Filed
Aug 02, 2023
Priority
Mar 04, 2021 — JP 2021-034477 +1 more
Examiner
LI, SUN M
Art Unit
2121
Tech Center
2100 — Computer Architecture & Software
Assignee
Hitachi Ltd.
OA Round
1 (Non-Final)
53%
Grant Probability
Moderate
1-2
OA Rounds
1y 1m
Est. Remaining
81%
With Interview

Examiner Intelligence

Grants 53% of resolved cases
53%
Career Allowance Rate
391 granted / 744 resolved
-2.4% vs TC avg
Strong +28% interview lift
Without
With
+28.1%
Interview Lift
resolved cases with interview
Typical timeline
4y 0m
Avg Prosecution
23 currently pending
Career history
763
Total Applications
across all art units

Statute-Specific Performance

§101
20.0%
-20.0% vs TC avg
§103
61.9%
+21.9% vs TC avg
§102
14.4%
-25.6% vs TC avg
§112
0.9%
-39.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 744 resolved cases

Office Action

§101
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 . The following is a non-final Office action on the merits in response to Application filed on 8/2/2023. Claims 14-24 are examined and pending. Response to Amendment The amendment filed on 8/2/2023 cancelled claim 1-13. No claim was previously cancelled. New claims 14-24 are added. No claim has been amended. Therefore, claims 14-24 are examined and allowed. Priority Acknowledgment is made of applicant's claim for foreign priority based on application filed in Japan (JP), filed 0n 3/4/2021, and the instant application is a cont. of PCT/JP2022/003656, filed 1/31/2022. Information Disclosure Statement The information disclosure statement (IDS) submitted on 8/2/2023, 10/11/2023, follows the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. 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 14-24 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. Alice Corp. also establishes that the same analysis should be used for all categories of claims, regardless of a system/apparatus, a method, or a product claim. The claimed invention (Claims 14-24) is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) abstract ideas including “Certain Methods of Organizing Human Activity”, “an idea “of itself”, which have been identified/found by the courts as abstract ideas in new 101 memos of the subject matter eligibility in here (https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility) including 2019 Revised Patent Subject Matter Eligibility Guidance. This judicial exception is not integrated into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because It/they is/are recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications: Independent claim 24 (Step 2A, Prong I): is directed to multiple abstract ideas including “Certain Methods of Organizing Human Activity”, and “Mental process”. Claim 24, Steps of, starting reconstruction of a machine learning model at a specified time within a certain day and changing a training period at fixed intervals within a specified period to construct a provisional machine learning model for each training period, determining the training period for the provisional machine learning model with the highest probability that a difference between the predicted value and the measured value of the time at which the patient is called is within a threshold value, which is an index of prediction accuracy, and reconstructing the machine learning model used in the task, after setting the determined training period. fall within “Certain Methods of Organizing Human Activity” grouping of abstract idea because these steps mainly describe the instant steps “collecting data, starting to construct a machine learning model, changing a training period, determining the training period, adjusting/reconstructing the machine learning model”, which are human activities and/or interactions between users/people/devices and therefore, certain methods of organizing human activity which encompasses both certain activity of a single person, certain activity that involves multiple people, and certain activity between a person and a computer. In addition, claim 24 steps mentioned above also falls within the abstract “Mental Processes” grouping of abstract ideas since these limitation covers performance of the limitations in the mind. For example, a human being can observe/collect/receive data, can observe/start to run an existing machine learning model, can observe/change the training period, can evaluate/determine the training period, can observe/rerun/change/adjust the Lachine learning model. Independent claim 24, Step 2A (Prong II): Accordingly, the claim recites an abstract idea(s) as pointed out above. This judicial exception(s) is/are not integrated into a practical application. In particular, the claim recites additional element (machine learning model). Other than reciting “a machine learning model “, nothing in the claim element precludes the step from practically being performed in the mind. There is no specificity regarding any technology, just broadly, execute the programming instructions to collect data, couple of databases to store data, run the data. Thus, the server, databases, are not an essential element to actually create, change, or display functionality, and is simply used as a tool to automate the mental tasks. Applicant simply use a generic processor/server/computing device as a tool to implement the abstract ideas. The Examiner notes the instant claimed invention is in fact merely carried out by a generically recited computing platform; that is, essentially any computing system as seen in the applicant’s specification. The additional element limitations are simply a field of use that attempt to limit the abstract idea to a particular technological environment. The type of information being manipulated does not impose meaningful limitations or render the idea less abstract. Further the courts have found that simply limiting the use of the abstract idea to a particular environment does not add significant more. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. There is neither improvement to another technology or technical field nor an improvement to the functioning of the computer itself, and does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Independent claim 24 (step 2B): There are additional elements (i.e. a machine learning model) in claim 24. This additional element is recited at high level of generality and are generic computing components, and add nothing of substance to the underlying abstract idea; thus, they are not significantly more than the identified abstract idea. These components are merely recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications; thus, they are not significantly more than the identified abstract idea. Generic computer/device components recited as performing generic computer functions that are well-understood, routine and convention activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to receive/transmit/present/display information does not impose any meaningful limit on the computer implementation of the abstract idea. At best, the claim(s) are merely providing an environment to implement the abstract idea. (see analysis in claim 24). According to MPEP 2106.05 (d), elements that the Courts have recognized as well-understood, routine, conventional activity in particular fields are e.g., "Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93” (evidence required by Berkeimer memo). Further, according to Berkheimer memo 04/19/2018, section III.A.1, “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)”. Applicant’s Specification, [0051—0056, 0090-0091] indicate a general-purpose computer perform the instant steps and demonstrates the well-understood, routine, conventional nature of the information processing device (a processor/a computer) in any computing implementation. In other word, in light of the description in the specification as mentioned above with respect to paras [0051—0056, 0090-0091]), the Specification demonstrates that the additional elements must be sufficiently well-known. Thus, evidence has been provided to show these additional elements are well-understood, routine, conventional activity according to Berkheimer memo. Therefore, for the above mentioned reasons, viewed as a whole, even in combination, the above steps do not amount to significantly more/do not provide an inventive concept. The procedural limitation “construct/reconstruct/trained machine learning model …” is specified at a high level of generality and is just recite as a name “machine learning model”. A person can use any “AI technique, for example, can put any information into an existing machine learning model and run the model”, and is simply organized information through human activity or merely mental tasks, and is part of, or a related, judicial exception and does not meaningfully limit the application of the identified judicial exception, and as such does not constitute significantly more. Furthermore, the reciting of “the machine learning model being trained…” merely using “machine learning” as a tool to perform an existing machine learning model/process and/or merely adding the words "apply it" to the judicial exception. See MPEP 2106.05(f). (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. (2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. (3) The particularity or generality of the application of the judicial exception. Thus, it is the solution of the abstract idea but not an improvement to another technology or technical field nor an improvement to the functioning of the computer itself. Applicant merely define a set of desirable results rather than defining a particular technology for achieving the set of desirable results. The Examiner notes the instant claimed invention is in fact merely carried out by a generically recited computing platform; that is, essentially any computing system as seen in the applicant’s specification. and as such does not constitute significantly more. Independent claims 14: Alice Corp. also establishes that the same analysis should be used for all categories of claims. Therefore, independent system claim 14 is also rejected as ineligible subject matter under 35 U.S.C. 101 for substantially the same reasons as the method claim(s) 24. Further, the components (i.e. a system, processor) described in independent claim 14, add nothing of substance to the underlying abstract idea. These components are merely recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications; thus, they are not significantly more than the identified abstract idea. Generic computer components recited as performing generic computer functions that are well-understood, routine and convention activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to receive/transmit/present/display information over communication network/internet does not impose any meaningful limit on the computer implementation of the abstract idea. At best, the claim(s) are merely providing an environment to implement the abstract idea. (see analysis in claim 24). Other than reciting “a system, a processor “, nothing in the claim element precludes the step from practically being performed in the mind. There is no additional element that are significant more than the abstract idea of collecting data, starting to construct a machine learning model, determining training period, modifying/adjusting the model. Thus, there is not an improvement to another technology or technical field nor an improvement to the functioning of the computer itself. Applicant merely define a set of desirable results rather than defining a particular technology for achieving the set of desirable results. The Examiner notes the instant claimed invention is in fact merely carried out by a generically recited computing platform; that is, essentially any computing system as seen in the applicant’s specification. and as such does not constitute significantly more. Dependent claims. 15-23, are merely add further details of the abstract steps/elements recited in claims 14 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, dependent claims 15-23 are also non-statutory subject matter. Viewed as a whole, the claims (14-24) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Thus, the claims do NOT recite limitations that are “significantly more” than the abstract idea because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Thus, the claimed invention, as a whole, does not provide 'significantly more' than the abstract idea, and is non-statutory subject matter. Prior Art Rejections A search of publicly available prior art fails to yield a reference or combination of references that would make the claimed combination obvious when considered as a whole. Independent claims 1, 15, 16, as a whole recite a combination of limitations that has Not been found as define over prior art of record (the combination of Bashir et al. (US 2020/0168305), Monaghan et al. (US 2021/0319905), Coulter et al. (US 2017/0235898), Gillies et al. (US 2023/0197281), Thomas et al. (US 2022/0336088), Makram et al. (US 2019/0180868), and THOMAS BEX GEORGE, EP-3716279-A1, and NPL1--Kim DY, Choi DS, Kim J, Chun SW, Gil HW, Cho NJ, Kang AR, Woo J. Developing an Individual Glucose Prediction Model Using Recurrent Neural Network. Sensors (Basel). 2020 Nov 12;20(22):6460. doi: 10.3390/s20226460. PMID: 33198170; PMCID: PMC7696446. NPL2--Hong WS, Haimovich AD, Taylor RA. Predicting hospital admission at emergency department triage using machine learning. PLoS One. 2018 Jul 20;13(7):e0201016. doi: 10.1371/journal.pone.0201016. PMID: 30028888; PMCID: PMC6054406. NPL3--F. Al-Rubaei and M. Alhanjouri, "Generalization of Deep Neural Network of Hospital Readmission Prediction Models for Diabetes Patients Using Apache Spark Clustering," 2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech), Gaza, Palestine, 2020, pp. 120-125, doi: 10.1109/iCareTech49914.2020.00030. All of the above references fail to teach all claimed features. Allowable Subject Matter As to the prior art rejections, in interpreting the claims, in light of the specification, upon further search and consideration, and for the reasons presented by the claims, the Examiner finds the claimed invention to be patentably distinct from the prior art of records. It is found that claim 14-24 are allowable subject to outstanding Alice 101 rejections. As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with, and pending remedy to outstanding 101 issues cited above. See 37 CFR 1.111(b) and MPEP § 707.07(a). The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Ishida (US 2019/0188598), teaches learning a learning model using first training data group that includes a part of remaining training data items obtained by excluding a test data group from a set of training data items. Prediction accuracy of the learning model is calculated using the test data group. Adhikari et al. (US 2023/0011880), teaches optimizing the discharge planning process for patients in a hospital. Thomas et al. (US 2021/0295987), teaches monitoring, predicting and/or alerting for census periods in medical inpatient units via employment of machine learning. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUN M LI whose telephone number is (571)270-5489. The examiner can normally be reached on Mon-Thurs, 8:30am--5pm. Fax is 571-270-6489. 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, Kambiz Abdi, can be reached on 571-272-6702. 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. /SUN M LI/Primary Examiner, Art Unit 3685
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Prosecution Timeline

Aug 02, 2023
Application Filed
Jul 01, 2026
Non-Final Rejection mailed — §101 (current)

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Prosecution Projections

1-2
Expected OA Rounds
53%
Grant Probability
81%
With Interview (+28.1%)
4y 0m (~1y 1m remaining)
Median Time to Grant
Low
PTA Risk
Based on 744 resolved cases by this examiner. Grant probability derived from career allowance rate.

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