# Jakob Nikolas Kather

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/jakob-nikolas-kather/

## Facts

| Field | Value |
| --- | --- |
| Citations | 21,043 |
| Field | Radiomics and Machine Learning in Medical Imaging |
| h-index | 74 |
| i10-index | 241 |
| Last Known Institution | University of Leeds |
| OpenAlex ID | https://openalex.org/A5073483894 |
| ORCID iD | https://orcid.org/0000-0002-3730-5348 |
| Works | 605 |

## Researcher papers

- [Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer](https://scholariq.org/papers/deep-learning-can-predict-microsatellite-instability-directly-from-histology-in/)
- [Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study](https://scholariq.org/papers/transformer-based-biomarker-prediction-from-colorectal-cancer-histology-a-large/)
- [Current applications and challenges in large language models for patient care: a systematic review](https://scholariq.org/papers/current-applications-and-challenges-in-large-language-models-for-patient-care-a/)
- [Swarm learning for decentralized artificial intelligence in cancer histopathology](https://scholariq.org/papers/swarm-learning-for-decentralized-artificial-intelligence-in-cancer/)

## Researcher topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Cancer Immunotherapy and Biomarkers](https://scholariq.org/topics/cancer-immunotherapy-and-biomarkers/)
- [Cancer Genomics and Diagnostics](https://scholariq.org/topics/cancer-genomics-and-diagnostics/)

## Researcher university

- [University of Leeds](https://scholariq.org/institutions/university-of-leeds/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.