Development and Validation of a Deep Learning-Based Microsatellite Instability Predictor from Prostate Cancer Whole-Slide Images

no code implementations • 12 Oct 2023 • Qiyuan Hu, Abbas A. Rizvi, Geoffery Schau, Kshitij Ingale, Yoni Muller, Rachel Baits, Sebastian Pretzer, Aïcha BenTaieb, Abigail Gordhamer, Roberto Nussenzveig, Adam Cole, Matthew O. Leavitt, Rohan P. Joshi, Nike Beaubier, Martin C. Stumpe, Kunal Nagpal

As such, prediction of MSI status from hematoxylin and eosin (H&E) stained whole-slide images (WSIs) could identify prostate cancer patients most likely to benefit from confirmatory testing and becoming eligible for immunotherapy.

Multiple Instance Learning whole slide images

Prediction of MET Overexpression in Non-Small Cell Lung Adenocarcinomas from Hematoxylin and Eosin Images

no code implementations • 11 Oct 2023 • Kshitij Ingale, Sun Hae Hong, Josh S. K. Bell, Abbas Rizvi, Amy Welch, Lingdao Sha, Irvin Ho, Kunal Nagpal, Aicha Bentaieb, Rohan P Joshi, Martin C Stumpe

MET protein overexpression is a targetable event in non-small cell lung cancer (NSCLC) and is the subject of active drug development.

Imaging-based histological features are predictive of MET alterations in Non-Small Cell Lung Cancer

no code implementations • 18 Mar 2022 • Rohan P. Joshi, Bolesław L. Osinski, Niha Beig, Lingdao Sha, Kshitij Ingale, Martin C. Stumpe

The association of individual cell features with MET alterations suggested a predictive model could distinguish MET wild-type from MET amplification or MET exon 14 deletion.

whole slide images