Kai-How Farh
24Patents
5h-index
23Co-inventors
61Inventor score
Filing activity: Aug 22, 2016 → Sep 29, 2023
Most-cited inventions
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US10423861B2 | Deep learning-based techniques for training deep convolutional neural networks | Emerging Cross-Sectional Technologies | 39 | Active |
| USD875773S1 | Display screen or portion thereof with graphical user interface | General | 31 | Active |
| US10540591B2 | Deep learning-based techniques for pre-training deep convolutional neural networks | Physics | 26 | Active |
| USD869489S1 | Display screen or portion thereof with graphical user interface | General | 16 | Active |
| USD829738S1 | Display screen or portion thereof with graphical user interface | General | 16 | Active |
| US11315016B2 | Deep convolutional neural networks for variant classification | Emerging Cross-Sectional Technologies | 3 | Active |
| US10558915B2 | Deep learning-based techniques for training deep convolutional neural networks | Emerging Cross-Sectional Technologies | 3 | Active |
| US10509795B2 | Semantic distance systems and methods for determining related ontological data | Physics | 2 | Active |
| US11488009B2 | Deep learning-based splice site classification | Physics | 2 | Active |
| US11538555B1 | Protein structure-based protein language models | Physics | 1 | Active |
| US11397889B2 | Aberrant splicing detection using convolutional neural networks (CNNs) | Physics | 1 | Active |
| US10607156B2 | Federated systems and methods for medical data sharing | Electricity | 1 | Active |
| US11515010B2 | Deep convolutional neural networks to predict variant pathogenicity using three-dimensional (3D) protein structures | Physics | 0 | Active |
| US11875237B2 | Federated systems and methods for medical data sharing | Electricity | 0 | Active |
| US11705219B2 | Deep learning-based variant classifier | Physics | 0 | Active |
| US11798650B2 | Semi-supervised learning for training an ensemble of deep convolutional neural networks | Emerging Cross-Sectional Technologies | 0 | Active |
| US12073922B2 | Deep learning-based framework for identifying sequence patterns that cause sequence-specific errors (SSEs) | Physics | 0 | Active |
| US11244246B2 | Federated systems and methods for medical data sharing | Electricity | 0 | Active |
| US11837324B2 | Deep learning-based aberrant splicing detection | Physics | 0 | Active |
| US11861491B2 | Deep learning-based pathogenicity classifier for promoter single nucleotide variants (pSNVs) | Physics | 0 | Active |
| US11386324B2 | Recurrent neural network-based variant pathogenicity classifier | Emerging Cross-Sectional Technologies | 0 | Active |
| US12217832B2 | Deep learning-based variant classifier | Physics | 0 | Active |
| US12165742B2 | Splicing site classification using neural networks | Physics | 0 | Active |
| US12217829B2 | Artificial intelligence-based analysis of protein three-dimensional (3D) structures | Physics | 0 | Active |
Source: USPTO / EPO open patent data. Inventor disambiguation is heuristic; counts are objective bibliographic measures.