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Can AI Catch What Clinicians Miss? A Comparative Study of Diagnostic Accuracy

Can AI Catch What Clinicians Miss? A Comparative Study of Diagnostic Accuracy

MLOps: From Model to Production

MLOps: From Model to Production

Cross-Validation: The Gold Standard for Model Evaluation

Cross-Validation: The Gold Standard for Model Evaluation

Support Vector Machines: Maximizing the Margin

Support Vector Machines: Maximizing the Margin

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Johns Hopkins Public Health Collective

Johns Hopkins Public Health Collective

18 Posts

Students writing cool things in Public Health and AI.

Cathy Zhang

Cathy Zhang

I'm currently a senior at Johns Hopkins University, majoring in Environmental Science and Public Health.

Rainie Li

Rainie Li

Ms. Li has 8 years of professional experience in Data Analysis, SAS programming, and Statistics in the healthcare, insurance and federal government contracting industries. Currently she works as a Senior Data Scientist Lead to support CMS Program Integrity Modeling & Analytic Support Contract (PIMASC) Contract to develop and maintain fraud detection algorithms for Fraud Prevention System.

Xiaoyi (Showry) Peng

Xiaoyi (Showry) Peng

1 Post

AI researcher and co-author of "Can AI Catch What Clinicians Miss?"

Yuhan Xiao

Yuhan Xiao

I'm a first-year ScM student in Biostatistics at Johns Hopkins Bloomberg School of Public Health. My research interests focus on real-world evidence (RWE), precision medicine, and clinical trials.