Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18746921 | PERSONALIZING PRESET MEAL SIZES IN INSULIN DELIVERY SYSTEM | June 2024 | October 2025 | Allow | 16 | 0 | 0 | Yes | No |
| 18630507 | READER MODE-OPTIMIZED ATTENTION APPLICATION | April 2024 | December 2025 | Allow | 20 | 2 | 0 | Yes | No |
| 18607340 | SYSTEMS AND METHODS FOR GENERATING SOCIAL ASSETS FROM ELECTRONIC PUBLICATIONS | March 2024 | March 2025 | Allow | 12 | 1 | 0 | No | No |
| 18598822 | ANALYSIS AND RESTRUCTURING OF WEB PAGES OF A WEB SITE | March 2024 | September 2024 | Allow | 7 | 0 | 0 | Yes | No |
| 18537581 | Interfaces and Techniques for Audio Content Access and Playback | December 2023 | August 2024 | Allow | 8 | 1 | 0 | Yes | No |
| 18243183 | STYLING A QUERY RESPONSE BASED ON A SUBJECT IDENTIFIED IN THE QUERY | September 2023 | May 2025 | Allow | 20 | 3 | 0 | Yes | No |
| 18230838 | SERVER-BASED ELECTRONIC PUBLICATION MANAGEMENT | August 2023 | November 2024 | Allow | 15 | 1 | 0 | Yes | No |
| 18354160 | OBTAINING AN ELECTRONIC SIGNATURE | July 2023 | July 2024 | Allow | 12 | 1 | 0 | No | No |
| 18334093 | DOCUMENT PROCESSING METHOD AND APPARATUS, AND ELECTRONIC DEVICE | June 2023 | September 2024 | Allow | 15 | 3 | 0 | Yes | No |
| 18297619 | METHOD, SYSTEM, AND COMPUTER DEVICE FOR GENERATING PORTAL PAGES | April 2023 | January 2025 | Abandon | 22 | 3 | 0 | Yes | No |
| 18164432 | AUTOMATED GENERATION OF DISPLAY LAYOUTS | February 2023 | December 2024 | Allow | 23 | 3 | 0 | Yes | No |
| 17993766 | GAMEPLANS FOR IMPROVED DECISION-MAKING | November 2022 | October 2024 | Allow | 25 | 2 | 0 | Yes | No |
| 17990854 | USER-SELECTABLE LINK INCLUDING MULTIPLE ROUTING LINKS | November 2022 | August 2024 | Allow | 21 | 2 | 0 | Yes | No |
| 17978864 | DYNAMICALLY GENERATING A STRUCTURED PAGE BASED ON USER INPUT | November 2022 | September 2025 | Allow | 34 | 4 | 0 | Yes | No |
| 17915929 | METHOD AND SYSTEM FOR CONSOLIDATING HETEROGENEOUS ELECTRONIC HEALTH DATA | September 2022 | October 2025 | Allow | 36 | 0 | 0 | No | No |
| 17862498 | MEASURING THE READABILITY OF WEBSITE PAGES | July 2022 | October 2024 | Allow | 27 | 1 | 0 | No | No |
| 17842377 | System and Method for Reviewing and Evaluating Discrepancies Between Two or More Documents | June 2022 | December 2024 | Allow | 30 | 3 | 0 | Yes | No |
| 17745617 | INTELLIGENT DEVICE SELECTION USING HISTORICAL INTERACTIONS | May 2022 | June 2025 | Allow | 37 | 0 | 0 | Yes | No |
| 17738195 | FACILITATING SELECTION OF KEYS RELATED TO A SELECTED KEY | May 2022 | December 2024 | Allow | 32 | 4 | 0 | Yes | No |
| 17732874 | MOLECULAR PROPERTY PREDICTION USING EDGE-INFORMATION FUSED GLOBAL GRAPH-READ NEURAL NETWORK FUNCTION | April 2022 | July 2025 | Allow | 39 | 1 | 0 | No | No |
| 17659794 | AI-BASED VIDEO ANALYSIS OF CATARACT SURGERY FOR DYNAMIC ANOMALY RECOGNITION AND CORRECTION | April 2022 | August 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17717184 | INFERENCE METHOD AND INFORMATION PROCESSING APPARATUS | April 2022 | January 2026 | Allow | 46 | 2 | 0 | No | No |
| 17715687 | DETERMINATION METHOD, NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM, AND INFORMATION PROCESSING DEVICE | April 2022 | September 2025 | Abandon | 42 | 1 | 0 | No | No |
| 17711831 | HYBRID APPROACH FOR GENERATING RECOMMENDATIONS | April 2022 | August 2024 | Allow | 29 | 3 | 0 | Yes | No |
| 17657606 | MACHINE LEARNING MODEL PROCESSING BASED ON PERPLEXITY | March 2022 | October 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17708819 | MULTIPLE INSTANCE LEARNER FOR TISSUE IMAGE CLASSIFICATION | March 2022 | January 2026 | Allow | 46 | 1 | 0 | No | No |
| 17677996 | METHODS AND SYSTEMS TO APPLY DIGITAL INTERVENTIONS BASED ON MACHINE LEARNING MODEL OUTPUT | February 2022 | September 2025 | Abandon | 43 | 1 | 0 | No | No |
| 17671406 | MACHINE LEARNING DENTAL SEGMENTATION SYSTEM AND METHODS USING GRAPH-BASED APPROACHES | February 2022 | November 2025 | Allow | 45 | 1 | 0 | Yes | No |
| 17584161 | GENERATING A CONFIGURATION PORTFOLIO INCLUDING A SET OF MODEL CONFIGURATIONS | January 2022 | December 2025 | Allow | 47 | 1 | 0 | Yes | No |
| 17554994 | TLS-BASED OPTIMIZATION OF STARK TONE TUNING | December 2021 | October 2025 | Allow | 46 | 1 | 0 | Yes | No |
| 17549375 | SYSTEM AND METHOD FOR CUSTOMIZED WEBSITE CONTENT AUTOMATION | December 2021 | February 2025 | Abandon | 38 | 4 | 0 | Yes | Yes |
| 17530852 | Efficient Neural Network Accelerator Dataflows | November 2021 | June 2025 | Allow | 43 | 0 | 0 | No | No |
| 17529584 | MACHINE LEARNING ENABLED SUPPLIER DATA ASSOCIATION | November 2021 | February 2026 | Allow | 51 | 3 | 0 | Yes | No |
| 17514350 | METHOD OF EXECUTING CLASSIFICATION PROCESS USING MACHINE LEARNING MODEL, INFORMATION PROCESSING DEVICE, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM STORING COMPUTER PROGRAM | October 2021 | August 2025 | Allow | 46 | 1 | 0 | Yes | No |
| 17508592 | TRAINING DEVICE, INFERRING DEVICE, TRAINING METHOD, INFERRING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM | October 2021 | October 2025 | Allow | 48 | 1 | 0 | No | No |
| 17497852 | INTERACTIVE SUBGROUP DISCOVERY | October 2021 | October 2025 | Allow | 49 | 1 | 0 | No | No |
| 17492046 | Approximate Bayesian Logistic Regression For Sparse Online Learning | October 2021 | November 2025 | Abandon | 50 | 1 | 0 | Yes | No |
| 17442437 | Automatic Extraction of Assets Data from Engineering Data Sources for Generating an HMI | September 2021 | July 2025 | Allow | 45 | 1 | 0 | No | No |
| 17390764 | TECHNIQUES FOR ADAPTING NEURAL NETWORKS TO DEVICES | July 2021 | September 2025 | Abandon | 50 | 1 | 0 | No | No |
| 17305372 | GRAPHICAL STUDY DESIGN FOR CLINICAL RESEARCH STUDY SYSTEMS | July 2021 | February 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17328124 | NEURAL NETWORK BASED TRAINING METHOD, INFERENCE METHOD AND APPARATUS | May 2021 | February 2026 | Allow | 56 | 2 | 0 | Yes | No |
| 17328427 | FEATURE SELECTION BASED ON UNSUPERVISED LEARNING | May 2021 | November 2025 | Abandon | 54 | 2 | 0 | Yes | No |
| 17236794 | ENVIRONMENT-SPECIFIC TRAINING OF MACHINE LEARNING MODELS | April 2021 | May 2025 | Allow | 49 | 2 | 0 | Yes | No |
| 17236647 | CONVOLUTIONAL NEURAL NETWORK ARCHITECTURES BASED ON SYNAPTIC CONNECTIVITY | April 2021 | April 2025 | Abandon | 48 | 1 | 0 | No | No |
| 17236892 | SYSTEM AND METHOD FOR ASSIGNING PERFORMANCE DEFECTS TO SOFTWARE PROCESSING COMPONENTS | April 2021 | September 2025 | Allow | 52 | 2 | 0 | Yes | No |
| 17221706 | TECHNIQUE FOR GENERATING DIGITAL CERTIFICATES | April 2021 | November 2024 | Abandon | 44 | 4 | 0 | Yes | No |
| 17150524 | CLASSIFIER ASSISTANCE USING DOMAIN-TRAINED EMBEDDING | January 2021 | December 2024 | Allow | 47 | 1 | 0 | Yes | No |
| 17148860 | CLASSIFICATION ALGORITHM BASED ON MULTIFORM SEPARATION | January 2021 | October 2024 | Allow | 45 | 1 | 0 | No | No |
| 17121990 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM, FOR RECOGNITION PROCESSING | December 2020 | May 2025 | Abandon | 53 | 2 | 0 | No | No |
| 17121702 | PRIVATE COMPUTATION OF AN AGENT DATA ATTRIBUTION SCORE IN COLLABORATED TASK | December 2020 | April 2025 | Allow | 52 | 2 | 0 | Yes | No |
| 17106013 | STAGED BIAS MEASUREMENTS IN MACHINE LEARNING PIPELINES | November 2020 | October 2025 | Allow | 58 | 4 | 0 | Yes | No |
| 17106021 | GENERATING VIEWS FOR BIAS METRICS AND FEATURE ATTRIBUTION CAPTURED IN MACHINE LEARNING PIPELINES | November 2020 | October 2025 | Allow | 59 | 4 | 0 | Yes | No |
| 16953095 | SYSTEM AND METHOD FOR SHARING AN INCREMENTALLY TRAINED MACHINE LEARNING (ML) MODEL FROM AN EDGE DEVICE TO ONE OR MORE OTHER EDGE DEVICES IN A PEER TO PEER NETWORK | November 2020 | December 2024 | Allow | 48 | 2 | 0 | Yes | No |
| 17092345 | LEVERAGING STRUCTURED DATA TO RANK UNSTRUCTURED DATA | November 2020 | April 2025 | Allow | 53 | 5 | 0 | Yes | No |
| 17044399 | PATTERN RECOGNITION APPARATUS, PATTERN RECOGNITION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM | October 2020 | August 2024 | Allow | 47 | 1 | 0 | No | No |
| 16942652 | AUTOMATED DOCUMENT TAGGING IN A DIGITAL MANAGEMENT PLATFORM | July 2020 | August 2024 | Allow | 49 | 6 | 0 | Yes | Yes |
| 16933930 | ENTERPRISE KNOWLEDGE GRAPHS USING USER-BASED MINING | July 2020 | August 2024 | Allow | 49 | 2 | 0 | Yes | No |
| 16802897 | CREATING DESCRIPTORS FOR BUSINESS ANALYTICS APPLICATIONS | February 2020 | October 2024 | Allow | 56 | 2 | 0 | Yes | Yes |
| 15980077 | WEB CONTENT MANAGEMENT DRIVEN COLLABORATIVE ACTIVITIES SYSTEM AND METHOD | May 2018 | September 2018 | Allow | 4 | 0 | 0 | No | No |
| 15707339 | SYSTEMS AND METHODS FOR GENERATING CONTENT | September 2017 | July 2019 | Allow | 22 | 1 | 0 | Yes | No |
| 15545681 | IDENTIFICATION OF A BREAKPOINT BASED ON A CORRELATION MEASUREMENT | July 2017 | March 2019 | Allow | 19 | 2 | 0 | Yes | No |
| 15545110 | High Quality Setting of Text for Print, With Full Control Over Layout, Using a Web Browser | July 2017 | April 2019 | Allow | 20 | 2 | 0 | Yes | No |
| 15412078 | BROWSER BOOKMARKING FOR MULTIPLE ENVIRONMENTS | January 2017 | May 2017 | Allow | 4 | 0 | 0 | No | No |
| 15128153 | CASCADING STYLE SHEET META LANGUAGE PERFORMANCE | September 2016 | March 2019 | Allow | 30 | 3 | 0 | Yes | No |
| 15218100 | BROWSER BOOKMARKING FOR MULTIPLE ENVIRONMENTS | July 2016 | April 2017 | Allow | 9 | 1 | 0 | No | No |
| 15062264 | BROWSER BOOKMARKING FOR MULTIPLE ENVIRONMENTS | March 2016 | June 2016 | Allow | 3 | 0 | 0 | No | No |
| 14657295 | SINGLE CLICK IN A PARTIALLY PROTECTED CELL OF A TABLE | March 2015 | February 2017 | Allow | 23 | 1 | 0 | Yes | No |
| 14586407 | METHOD FOR GENERATING RANDOM CONTENT FOR AN ARTICLE | December 2014 | May 2017 | Allow | 28 | 1 | 0 | No | No |
| 14499327 | WEB CONTENT MANAGEMENT DRIVEN COLLABORATIVE ACTIVITIES SYSTEM AND METHOD | September 2014 | April 2018 | Allow | 42 | 7 | 0 | Yes | No |
| 14487258 | Exposing Fragment Identifiers | September 2014 | April 2017 | Allow | 31 | 4 | 0 | Yes | No |
| 14487301 | PLAYBACK SYSTEM FOR SYNCHRONISED SOUNDTRACKS FOR ELECTRONIC MEDIA CONTENT | September 2014 | October 2017 | Allow | 37 | 2 | 0 | Yes | No |
| 14167412 | WEB CONTENT MANAGEMENT DRIVEN COLLABORATIVE ACTIVITIES SYSTEM AND METHOD | January 2014 | April 2018 | Allow | 50 | 6 | 0 | Yes | No |
| 13800154 | WEB PAGE DESIGN SCANNER | March 2013 | December 2018 | Allow | 60 | 7 | 0 | Yes | No |
| 13727888 | FACILITATING WEBPAGE NAVIGATION | December 2012 | January 2017 | Allow | 48 | 5 | 0 | Yes | No |
| 13727390 | SUMMARY VIEW OF A PROFILE | December 2012 | March 2016 | Allow | 38 | 3 | 0 | No | No |
| 13631606 | GENERATING DOCUMENT CONTENT FROM APPLICATION DATA | September 2012 | June 2016 | Allow | 45 | 3 | 0 | Yes | No |
| 13565016 | INPUTTING IN A TEXTBOX | August 2012 | November 2015 | Allow | 39 | 2 | 0 | Yes | No |
| 13526373 | Composing the Display of a Virtualized Web Browser | June 2012 | July 2015 | Allow | 37 | 2 | 0 | Yes | No |
| 13281999 | MASKING PARTIAL TEXT DATA IN DIGITAL DOCUMENT | October 2011 | March 2016 | Allow | 53 | 2 | 0 | Yes | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner ROY, SANCHITA.
With a 100.0% reversal rate, the PTAB has reversed the examiner's rejections more often than affirming them. This reversal rate is in the top 25% across the USPTO, indicating that appeals are more successful here than in most other areas.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 33.3% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is above the USPTO average, suggesting that filing an appeal can be an effective strategy for prompting reconsideration.
✓ Appeals to PTAB show good success rates. If you have a strong case on the merits, consider fully prosecuting the appeal to a Board decision.
✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
Examiner ROY, SANCHITA works in Art Unit 2146 and has examined 50 patent applications in our dataset. With an allowance rate of 86.0%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 47 months.
Examiner ROY, SANCHITA's allowance rate of 86.0% places them in the 63% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by ROY, SANCHITA receive 2.28 office actions before reaching final disposition. This places the examiner in the 64% percentile for office actions issued. This examiner issues a slightly above-average number of office actions.
The median time to disposition (half-life) for applications examined by ROY, SANCHITA is 47 months. This places the examiner in the 9% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +8.6% benefit to allowance rate for applications examined by ROY, SANCHITA. This interview benefit is in the 39% percentile among all examiners. Recommendation: Interviews provide a below-average benefit with this examiner.
When applicants file an RCE with this examiner, 32.9% of applications are subsequently allowed. This success rate is in the 70% percentile among all examiners. Strategic Insight: RCEs show above-average effectiveness with this examiner. Consider whether your amendments or new arguments are strong enough to warrant an RCE versus filing a continuation.
This examiner enters after-final amendments leading to allowance in 0.0% of cases where such amendments are filed. This entry rate is in the 1% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
When applicants request a pre-appeal conference (PAC) with this examiner, 0.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 6% percentile among all examiners. Note: Pre-appeal conferences show limited success with this examiner compared to others. While still worth considering, be prepared to proceed with a full appeal brief if the PAC does not result in favorable action.
This examiner withdraws rejections or reopens prosecution in 66.7% of appeals filed. This is in the 48% percentile among all examiners. Strategic Insight: This examiner shows below-average willingness to reconsider rejections during appeals. Be prepared to fully prosecute appeals if filed.
When applicants file petitions regarding this examiner's actions, 60.0% are granted (fully or in part). This grant rate is in the 64% percentile among all examiners. Strategic Note: Petitions show above-average success regarding this examiner's actions. Petitionable matters include restriction requirements (MPEP § 1002.02(c)(2)) and various procedural issues.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 11% percentile). This examiner rarely makes examiner's amendments compared to other examiners. You should expect to make all necessary claim amendments yourself through formal amendment practice.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 11% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.