Stanford University
Showing 381-390 of 565 Results
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Scott Dixon
Professor of Biology
Current Research and Scholarly InterestsMy lab is interested in the relationship between cell death and metabolism. Using techniques drawn from many disciplines my laboratory is investigating how perturbation of intracellular metabolic networks can result in novel forms of cell death, such as ferroptosis. We are interested in applying this knowledge to find new ways to treat diseases characterized by insufficient (e.g. cancer) or excessive (e.g. neurodegeneration) cell death.
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Bao Do
Clinical Professor, Radiology
BioBao Do is an expert in radiology informatics, computer vision, and quantitative musculoskeletal imaging. He has developed and validated deep-learning models for diagnostic interpretation, hardware recognition, and automated reporting across orthopedic and radiographic domains. His recent studies demonstrated high-performance CNNs for detecting perilunate and lunate dislocations on wrist radiographs (AUC = 0.986) 【Pridgen et al., Plast Reconstr Surg 2023; 10.1097/PRS.0000000000010928】 and improving clinician accuracy through machine-learning-assisted diagnosis in a multicenter reader study 【Luan et al., Hand (N Y)2025; 10.1177/15589447241308603】. He co-developed AI systems for automated classification of hip hardware achieving radiologist-level accuracy (AUC ≥ 0.99) 【Ma et al., J Imaging Informat Med 2024; 10.1007/s10278-024-01263-y】, scoliosis curvature measurement from 2,150 spine radiographs 【Ha et al., J Digit Imaging 2022; 10.1007/s10278-022-00595-x】, and fully automated leg-length analysis and reporting 【Larson et al., J Digit Imaging2022; 10.1007/s10278-022-00671-2】. Earlier work included Bayesian models for bone tumor diagnosis 【Do et al., J Digit Imaging 2017; 30:709-13】, semantic content-based image retrieval using relevance feedback 【Banerjee et al., J Biomed Inform 2018; 84:123-35】, and NLP-based uncertainty detection in radiology reports 【Callen et al., J Digit Imaging 2020; 33:1209-19】, demonstrating a career-long commitment to explainable, data-driven imaging analytics.
Interests: Automation in medicine, quantitative MSK AI, MSK tumor AI, AI in workflow, and computer systems in education, QC, research
www.stanford.edu/~baodo -
Diana Do, MD
Professor of Ophthalmology
Current Research and Scholarly InterestsDr. Do's research focuses on collaborative clinical trials to investigate novel treatments for retinal vascular diseases and ocular inflammation. She performs research to develop state of the art therapies for age-related macular degeneration, diabetic eye disease, retinal vein occlusion, retinal inflammation, and retinal detachment.
