Efficient detection of rare clinical cohorts: a robust framework for extreme class imbalance in low-resource clinical text

Internal feasibility evaluation of SAM-Med3D for cervical cancer clinical target volume segmentation on planning computed tomography

The SAM-Med3D model was initialized from public pretrained weights and fine-tuned on the training cohort without architectural modification, then assessed with simulated/oracle-guided prompts at 1, 3, 5, 7, 9, and 11 clicks using Dice, HD95, 3-mm surface Dice, and volume consistency.

Formalizing method choice: a data-driven selection of mechanistic models for predicting human heart drug partitioning

We developed a workflow based on a human-derived dataset, aiming to predict the human heart-to-plasma partition coefficient, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsi...

Semi-supervised segmentation of intratumoral and peritumoral CT regions in head and neck cancer with limited annotations

Beyond the General Linear Model: Linear Mixed-Effects Modeling of fMRI Data from the Human Connectome Project

Ergodic robust maximisation of asymptotic growth with stochastic factor processes

We consider a robust asymptotic growth problem under model uncertainty in the presence of stochastic factors. We fix two inputs representing the instantaneous covariance for the asset price process X\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepa...

Explainable Federated Learning for Trustworthy Thoracic Disease Detection Under Non-IID Data Distributions

Comparison of SHAP and Grad-CAM attribution maps confirms clinically coherent disease-specific localisation, and reveals monotonic performance degradation, identifying minimal regularisation as optimal for multi-label medical imaging.