Khalid Abdul Jabbar

Abstract The assessment of tumor-infiltrating lymphocyte (TILs), together with gene expression signatures (GES), has the potential to guide personalized breast cancer therapy. We included 262 patients from the phase III NSABP B-41 trial, which evaluated neoadjuvant HER2-targeted therapies in combination with chemotherapy. We conducted a manual and artificial intelligence (AI)-based analyses of TILs, as well as GES from RNA sequencing.

Abstract Cancers occur across species. Understanding what is consistent and varies across species can provide new insights into cancer initiation and evolution, with significant implications for animal welfare and wildlife conservation. We build a pan-species cancer digital pathology atlas (panspecies.ai) and conduct a pan-species study of computational comparative pathology using a supervised convolutional neural network algorithm trained on human samples.

Abstract The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods.