1 citations · 2 across the 3 of their papers we have counts for
4 papers
AI-augmented histopathologic review using image analysis to optimize DNA yield and tumor purity from FFPE slides
Bolesław L. Osinski, Aïcha BenTaieb, Irvin Ho +8
To achieve minimum DNA input and tumor purity requirements for next-generation sequencing (NGS), pathologists visually estimate macrodissection and slide count decisions. Misestima…
Imaging-based histological features are predictive of MET alterations in Non-Small Cell Lung Cancer
Rohan P. Joshi, Bolesław L. Osinski, Niha Beig +3
MET is a proto-oncogene whose somatic activation in non-small cell lung cancer leads to increased cell growth and tumor progression. The two major classes of MET alterations are ge…
Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
Nathaniel Braman, Jacob W. H. Gordon, Emery T. Goossens +3
Clinical decision-making in oncology involves multimodal data such as radiology scans, molecular profiling, histopathology slides, and clinical factors. Despite the importance of t…
Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
Sushravya Raghunath, Alvaro E. Ulloa Cerna, Linyuan Jing +12
The electrocardiogram (ECG) is a widely-used medical test, typically consisting of 12 voltage versus time traces collected from surface recordings over the heart. Here we hypothesi…