Prosecution Insights
Last updated: April 19, 2026
Application No. 19/257,693

INFORMATION PROCESSING APPARATUS AND NON-TRANSITORY COMPUTER READABLE MEDIUM

Non-Final OA §102
Filed
Jul 02, 2025
Examiner
LAM, VINH TANG
Art Unit
2628
Tech Center
2600 — Communications
Assignee
Agama-X Co., Ltd.
OA Round
1 (Non-Final)
72%
Grant Probability
Favorable
1-2
OA Rounds
2y 8m
To Grant
81%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allow Rate
471 granted / 655 resolved
+9.9% vs TC avg
Moderate +9% lift
Without
With
+9.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
25 currently pending
Career history
680
Total Applications
across all art units

Statute-Specific Performance

§101
2.0%
-38.0% vs TC avg
§103
47.4%
+7.4% vs TC avg
§102
31.5%
-8.5% vs TC avg
§112
14.3%
-25.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 655 resolved cases

Office Action

§102
DETAILED ACTION Notice of Pre-AIA or AIA Status 1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. 2. Claim(s) 1-3 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chan et al. (US Patent/PGPub. No. 10733566). Regarding Claim 1, Chan et al. teach a method (Col. 1, Ln. 11-20, FIG. 1, i.e. method, and computer program product for receiving large quantities of real-time hospital data) comprising: by a processor (Col. 3, Ln. 62-66, FIG. 1, i.e. system comprising at least one processor), inputting (Col. 6, Ln. 31-40, FIG. 1, i.e. hospital or clinical data 103… which may then be inputted) into an artificial intelligence (Col. 6, Ln. 31-40, FIG. 1, i.e. parser 122 or machine learning systems) biological information (Col. 8, Ln. 11-20, FIG. 1, i.e. blood tests … x-rays … (MRI) … (CAT)) of an at least one living thing (Col. 8, Ln. 11-20, FIG. 1, i.e. specific patient), and context information (FIG. 5A, i.e. as shown by the figure(s) date and time at 516, 518, and 520) indicating a context associated with information about a time (FIG. 5A, i.e. as shown by the figure(s) at 516 indicates date and time “9/5/2016 20:41”) at which the biological information was measured (Col. 21, Ln. 57-62, FIG. 5A, i.e. glucose measurements 514 in entries 516, 518, and 520); and outputting information regarding a condition (Col. 21, Ln. 32-39, FIG. 5A, i.e. “Details” page, possible medical conditions for patient 502 are shown, including hyponatremia 508) of the at least one living thing (i.e. please see above citation(s)) based on a determination result (Col. 10, Ln. 52-64, FIG. 2A & 2B, i.e. sodium level, sodium chloride medication orders, and dehydration data) produced by the artificial intelligence (Col. 10, Ln. 52-64, FIG. 2A & 2B, i.e. models 210-240 may leverage … neural network models, deep learning models). Regarding Claim 2, Chan et al. teach a method (Col. 1, Ln. 11-20, FIG. 1, i.e. method, and computer program product for receiving large quantities of real-time hospital data) comprising: by a processor (Col. 3, Ln. 62-66, FIG. 1, i.e. system comprising at least one processor), inputting (Col. 6, Ln. 31-40, FIG. 1, i.e. hospital or clinical data 103… which may then be inputted) into an artificial intelligence (Col. 6, Ln. 31-40, FIG. 1, i.e. parser 122 or machine learning systems) biological information (Col. 8, Ln. 11-20, FIG. 1, i.e. blood tests … x-rays … (MRI) … (CAT)) of an at least one living thing (Col. 8, Ln. 11-20, FIG. 1, i.e. specific patient), and context information (FIG. 5A, i.e. as shown by the figure(s) date and time at 516, 518, and 520) indicating a context associated with information about a time (FIG. 5A, i.e. as shown by the figure(s) at 516 indicates date and time “9/5/2016 20:41”) at which the biological information was measured (Col. 21, Ln. 57-62, FIG. 5A, i.e. glucose measurements 514 in entries 516, 518, and 520); and outputting, based on a determination result (Col. 10, Ln. 52-64, FIG. 2A & 2B, i.e. sodium level, sodium chloride medication orders, and dehydration data) produced by the artificial intelligence (Col. 10, Ln. 52-64, FIG. 2A & 2B, i.e. models 210-240 may leverage … neural network models, deep learning models), information that needs to be reported among information (Col. 10, Ln. 52-64, FIG. 2A & 2B, i.e. sodium level, sodium chloride medication orders, and dehydration data) associated with temporal changes (Col. 21, Ln. 57-62, FIG. 5A, i.e. patient's current, minimum, and maximum glucose measurements 514 in entries 516, 518, and 520 (Please note changes in measurements associated with dates and times) of the at least one living thing (i.e. please see above citation(s)). Regarding Claim 3, Chan et al. teach the method according to claim 2, wherein the information that needs to be reported is information (i.e. please see above citation(s)) relating to a disease (Col. 21, Ln. 32-39, FIG. 5A, i.e. including hyponatremia 508). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to VINH TANG LAM whose telephone number is (571) 270-3704. The examiner can normally be reached Monday to Friday 8:00 AM to 5:00 PM. 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, Nitin K Patel can be reached at (571) 272-7677. 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. /VINH T LAM/Primary Examiner, Art Unit 2628
Read full office action

Prosecution Timeline

Jul 02, 2025
Application Filed
Mar 24, 2026
Non-Final Rejection — §102 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
72%
Grant Probability
81%
With Interview (+9.2%)
2y 8m
Median Time to Grant
Low
PTA Risk
Based on 655 resolved cases by this examiner. Grant probability derived from career allow rate.

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