IEEE

On-the-Fly Improving Segment Anything for Medical Image Segmentation Using Auxiliary Online Learning

Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...
IEEE

MLXOps4Medic: A Service Framework for Machine Learning and Explainability Operations in Medical Imaging AI Development

Integrating AI models with the medical domain is challenging as it involves more complex workflows compared to traditional machine learning operations (MLOps). Requirements such as model performance ...
Journal of Medical Internet Research

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

Objective: This study aimed to develop and evaluate a machine learning (ML)–based algorithm to predict whether an initial vancomycin dose falls within the therapeutic range of the 24-hour area under ...
Journal of Medical Internet Research

Text-Based Depression Prediction on Social Media Using Machine Learning: Systematic Review and Meta-Analysis

Additionally, the effects of social media platform type, machine learning approach, and use of outcome measures in depression prediction models need attention. Analyzing social media texts for ...