Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18657768 | RHYME ENGINE FOR LITERARY WORKS WITH RHYME OR RHYTHM | May 2024 | April 2025 | Allow | 11 | 1 | 0 | No | No |
| 18600118 | ENHANCED INTEGRATION OF SPREADSHEETS WITH EXTERNAL ENVIRONMENTS | March 2024 | May 2025 | Abandon | 14 | 1 | 0 | Yes | No |
| 18503131 | Methods and Systems for Providing Selective Multi-Way Replication and Atomization of Cell Blocks and Other Elements in Spreadsheets and Presentations | November 2023 | November 2024 | Allow | 12 | 0 | 0 | Yes | No |
| 18476060 | USING MACHINE LEARNING TO PREDICT PERFORMANCE OF SECURE DOCUMENTS | September 2023 | September 2024 | Allow | 12 | 1 | 0 | Yes | No |
| 18449397 | BROWSER-BASED NAVIGATION SUGGESTIONS FOR TASK COMPLETION | August 2023 | March 2025 | Allow | 19 | 2 | 0 | Yes | No |
| 18227359 | AUTOMATED DOCUMENT HIGHLIGHTING IN A DIGITAL MANAGEMENT PLATFORM | July 2023 | February 2025 | Allow | 18 | 2 | 0 | Yes | No |
| 18266735 | INFORMATION PROCESSING DEVICE, METHOD, PROGRAM, AND INFORMATION PROCESSING SYSTEM FOR ASSISTING IN EXAMINATION OF IMAGE FOR PRINTING | June 2023 | June 2025 | Allow | 24 | 1 | 0 | No | No |
| 18316213 | REDUCING INTERFERENCE BETWEEN TWO TEXTS | May 2023 | September 2024 | Allow | 16 | 3 | 1 | Yes | No |
| 18117222 | GUARDRAILS FOR EFFICIENT PROCESSING AND ERROR PREVENTION IN GENERATING SUGGESTED MESSAGES | March 2023 | July 2024 | Allow | 17 | 1 | 0 | Yes | No |
| 18106802 | STYLE TRANSFER | February 2023 | February 2024 | Allow | 12 | 3 | 0 | Yes | No |
| 18009592 | AUTOMATIC DATA EXTRACTION | December 2022 | June 2025 | Allow | 31 | 2 | 0 | No | No |
| 17993959 | METHOD OF PUBLISHING A COMPUTER FILE INCLUDING INTERACTIVE DATA AND A METHOD OF MANAGING SAID DATA | November 2022 | February 2025 | Abandon | 27 | 1 | 0 | No | No |
| 17833247 | TABLE COLUMN OPERATIONS FOR SPREADSHEETS | June 2022 | August 2024 | Allow | 27 | 3 | 0 | Yes | No |
| 17657573 | GENERATING AND UTILIZING DIGITAL MEDIA CLIPS BASED ON CONTEXTUAL METADATA FROM DIGITAL ENVIRONMENTS | March 2022 | September 2024 | Allow | 30 | 4 | 0 | Yes | No |
| 17653126 | SYSTEM AND METHOD FOR MULTI-DIMENSIONAL KNOWLEDGE REPRESENTATION | March 2022 | November 2024 | Abandon | 33 | 2 | 0 | No | Yes |
| 17670662 | METHODS AND SYSTEMS FOR GENERATING TRAINING DATA FOR COMPUTER-EXECUTABLE MACHINE LEARNING ALGORITHM WITHIN A COMPUTER-IMPLEMENTED CROWDSOURCE ENVIRONMENT | February 2022 | May 2025 | Allow | 39 | 1 | 0 | Yes | No |
| 17556218 | DEEP EMBEDDING LEARNING MODELS WITH MIMICRY EFFECT | December 2021 | June 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17619723 | LEARNING DEVICE, LEARNING METHOD, AND COMPUTER-READABLE MEDIUM | December 2021 | June 2025 | Abandon | 42 | 1 | 0 | Yes | No |
| 17457996 | SYSTEMS AND METHODS FOR FEDERATED LEARNING OPTIMIZATION VIA CLUSTER FEEDBACK | December 2021 | March 2025 | Allow | 39 | 0 | 0 | No | No |
| 17456898 | DOMAIN ADAPTATION | November 2021 | April 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17506161 | MACHINE LEARNING MODEL SCALING SYSTEM WITH ENERGY EFFICIENT NETWORK DATA TRANSFER FOR POWER AWARE HARDWARE | October 2021 | May 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17463673 | TESTING MODELS IN DATA PIPELINE | September 2021 | April 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17433724 | METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR CONTROLLING GENETIC LEARNING FOR PREDICTIVE MODELS USING PREDEFINED STRATEGIES | August 2021 | March 2025 | Allow | 43 | 1 | 0 | No | No |
| 17445620 | System and method for detecting anomalies in images | August 2021 | March 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17407427 | SYSTEM AND METHOD FOR PRINTING WITH IMPROVED CONTENT | August 2021 | January 2025 | Abandon | 41 | 3 | 0 | No | No |
| 17398296 | METHOD AND APPARATUS WITH NEURAL NETWORK OPERATION USING SPARSIFICATION | August 2021 | May 2025 | Allow | 45 | 2 | 0 | Yes | No |
| 17444773 | SYSTEM, TRAINING DEVICE, TRAINING METHOD, AND PREDICTING DEVICE | August 2021 | May 2025 | Abandon | 45 | 1 | 0 | No | No |
| 17444548 | STOCHASTIC COMPILATION OF MULTIPLEXED QUANTUM ROTATIONS | August 2021 | April 2025 | Allow | 44 | 1 | 0 | No | No |
| 17382121 | Noisy Concurrent Training for Training DNNs Efficiently Under Noisy Labels in a Collaborative Learning Framework | July 2021 | April 2025 | Abandon | 44 | 1 | 0 | No | No |
| 17419940 | METHOD FOR TRAINING AND OPERATING AN ARTIFICIAL NEURAL NETWORK CAPABLE OF MULTITASKING, ARTIFICIAL NEURAL NETWORK CAPABLE OF MULTITASKING, AND DEVICE | June 2021 | December 2024 | Allow | 41 | 1 | 0 | No | No |
| 17357602 | Edge Device Machine Learning | June 2021 | June 2025 | Allow | 47 | 2 | 0 | Yes | No |
| 17350537 | GENERALIZED MACHINE LEARNING APPLICATION TO ESTIMATE WHOLESALE REFINED PRODUCT PRICE SEMI-ELASTICITIES | June 2021 | February 2025 | Abandon | 44 | 1 | 0 | No | No |
| 17334613 | DATA-AWARE MODEL PRUNING FOR NEURAL NETWORKS | May 2021 | January 2025 | Allow | 44 | 1 | 0 | Yes | No |
| 17244947 | METHOD FOR EVALUATING MECHANICAL STATE OF HIGH-VOLTAGE SHUNT REACTOR BASED ON VIBRATION CHARACTERISTICS | April 2021 | October 2024 | Allow | 42 | 1 | 0 | Yes | No |
| 17244480 | PARAMETERIZED NEIGHBORHOOD MEMORY ADAPTATION | April 2021 | September 2024 | Allow | 40 | 1 | 0 | Yes | No |
| 17204670 | METHODS AND SYSTEMS FOR CROSS-DOMAIN FEW-SHOT CLASSIFICATION | March 2021 | September 2024 | Allow | 42 | 1 | 0 | Yes | No |
| 17249051 | PROVIDING ENHANCED FUNCTIONALITY IN AN INTERACTIVE ELECTRONIC TECHNICAL MANUAL | February 2021 | January 2025 | Abandon | 47 | 6 | 0 | No | No |
| 17163513 | NEURAL NETWORK UNIT | January 2021 | November 2024 | Allow | 46 | 1 | 0 | No | No |
| 17256855 | A NEURAL NETWORK QUANTIZATION DATA PROCESSING METHOD, DEVICE, COMPUTER EQUIPMENT AND STORAGE MEDIUM | December 2020 | August 2024 | Allow | 43 | 1 | 0 | No | No |
| 15734365 | DATA ANALYSIS SYSTEM AND DATA ANALYSIS METHOD | December 2020 | March 2025 | Abandon | 51 | 3 | 0 | Yes | No |
| 17066916 | EFFICIENT SYNTHESIS OF OPTIMAL MULTI-QUBIT CLIFFORD CIRCUITS | October 2020 | January 2025 | Allow | 51 | 2 | 1 | Yes | No |
| 15891563 | NOVEL ARABIC SPELL CHECKING ERROR MODEL | February 2018 | October 2019 | Allow | 21 | 1 | 0 | Yes | No |
| 15025513 | METHOD AND SYSTEM FOR SELECTING ENCODING FORMAT FOR READING TARGET DOCUMENT | March 2016 | March 2019 | Allow | 36 | 2 | 0 | No | No |
| 14987261 | CONVERSION OF A PRESENTATION TO DARWIN INFORMATION TYPING ARCHITECTURE (DITA) | January 2016 | January 2018 | Allow | 24 | 1 | 0 | No | No |
| 14202718 | CONVERSION OF A PRESENTATION TO DARWIN INFORMATION TYPING ARCHITECTURE (DITA) | March 2014 | September 2015 | Allow | 19 | 1 | 0 | No | No |
| 14090184 | DISCOVERING RELATIONSHIPS IN TABULAR DATA | November 2013 | October 2016 | Allow | 35 | 4 | 0 | Yes | No |
| 13933525 | APPARATUS AND METHOD FOR GENERATING INSPECTION REPORT(S) | July 2013 | May 2018 | Allow | 59 | 5 | 0 | No | No |
| 13932435 | Discovering Relationships in Tabular Data | July 2013 | August 2016 | Allow | 37 | 3 | 0 | No | No |
| 13930324 | APPARATUS, CONTROL METHOD THEREOF, AND STORAGE MEDIUM THAT DETERMINE A LAYOUT IMAGE FROM A GENERATED PLURALITY OF LAYOUT IMAGES BY EVALUATING SELECTED TARGET IMAGES | June 2013 | March 2018 | Allow | 56 | 5 | 0 | Yes | No |
| 13658069 | CONVERSION OF A PRESENTATION TO DARWIN INFORMATION TYPING ARCHITECTURE (DITA) | October 2012 | September 2015 | Allow | 35 | 1 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner LEVEL, BARBARA HENRY.
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, 0.0% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is in the bottom 25% across the USPTO, indicating that filing appeals is less effective here than in most other areas.
⚠ Filing a Notice of Appeal shows limited benefit. Consider other strategies like interviews or amendments before appealing.
Examiner LEVEL, BARBARA HENRY works in Art Unit 2142 and has examined 48 patent applications in our dataset. With an allowance rate of 81.2%, this examiner has a below-average tendency to allow applications. Applications typically reach final disposition in approximately 41 months.
Examiner LEVEL, BARBARA HENRY's allowance rate of 81.2% places them in the 46% percentile among all USPTO examiners. This examiner has a below-average tendency to allow applications.
On average, applications examined by LEVEL, BARBARA HENRY receive 1.77 office actions before reaching final disposition. This places the examiner in the 53% 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 LEVEL, BARBARA HENRY is 41 months. This places the examiner in the 6% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +25.9% benefit to allowance rate for applications examined by LEVEL, BARBARA HENRY. This interview benefit is in the 76% percentile among all examiners. Recommendation: Interviews are highly effective with this examiner and should be strongly considered as a prosecution strategy. Per MPEP § 713.10, interviews are available at any time before the Notice of Allowance is mailed or jurisdiction transfers to the PTAB.
When applicants file an RCE with this examiner, 32.0% of applications are subsequently allowed. This success rate is in the 59% 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 25.0% of cases where such amendments are filed. This entry rate is in the 25% percentile among all examiners. Strategic Recommendation: This examiner shows below-average receptiveness to after-final amendments. You may need to file an RCE or appeal rather than relying on after-final amendment entry.
When applicants file petitions regarding this examiner's actions, 100.0% are granted (fully or in part). This grant rate is in the 96% percentile among all examiners. Strategic Note: Petitions are frequently granted regarding this examiner's actions compared to other examiners. Per MPEP § 1002.02(c), various examiner actions are petitionable to the Technology Center Director, including prematureness of final rejection, refusal to enter amendments, and requirement for information. If you believe an examiner action is improper, consider filing a petition.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 9% 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 10% 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.