# Babak Ehteshami Bejnordi

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/babak-ehteshami-bejnordi/

## Facts

| Field | Value |
| --- | --- |
| Citations | 21,111 |
| Field | AI in cancer detection |
| h-index | 21 |
| i10-index | 27 |
| Last Known Institution | Qualcomm (United Kingdom) |
| OpenAlex ID | https://openalex.org/A5055531734 |
| ORCID iD | https://orcid.org/0000-0002-6258-5687 |
| Works | 64 |

## Researcher papers

- [From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge](https://scholariq.org/papers/from-detection-of-individual-metastases-to-classification-of-lymph-node-status/)
- [Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies](https://scholariq.org/papers/using-deep-convolutional-neural-networks-to-identify-and-classify-tumor/)

## Researcher topics

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)

## Researcher university

- [Qualcomm (United Kingdom)](https://scholariq.org/institutions/qualcomm-united-kingdom/)

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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.