240 citations · 252 across the 5 of their papers we have counts for
5 papers
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis
Roxana Daneshjou, Mert Yuksekgonul, Zhuo Ran Cai +2
For the deployment of artificial intelligence (AI) in high-risk settings, such as healthcare, methods that provide interpretability/explainability or allow fine-grained error analy…
Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality
Kailas Vodrahalli, Justin Ko, Albert S. Chiou +7
Telemedicine utilization was accelerated during the COVID-19 pandemic, and skin conditions were a common use case. However, the quality of photographs sent by patients remains a ma…
Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality
David Ouyang, John Theurer, Nathan R. Stein +21
Background. Pre-operative risk assessments used in clinical practice are limited in their ability to identify risk for post-operative mortality. We hypothesize that electrocardiogr…
CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq
Bryan He, Matthew Thomson, Meena Subramaniam +3
Single-cell RNA sequencing (scRNA-seq) has the potential to provide powerful, high-resolution signatures to inform disease prognosis and precision medicine. This paper takes an imp…
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning
Grant Duffy, Paul P Cheng, Neal Yuan +15
Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrop…