Journal of Medical Internet Research

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

Conclusions: This study represents a pioneering effort in using LLMs, particularly GPT-4.0, to construct a comprehensive sepsis knowledge graph. The innovative application of prompt engineering, ...
IEEE

Spectral Structure-Aware Initialization and Probability-Consistent Self-Training for Cross-Scene Hyperspectral Image Classification

Abstract: Cross-scene classification of hyperspectral images (HSIs) aims to classify target domain (TD) data using only labeled source domain (SD) data and unlabeled TD data during training. However, ...

New framework renders AI more trustworthy for cancer subtyping

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
IEEE

Hierarchy-Aware and Knowledge-Guided Learning for Multi-Label Classification of Retinal Diseases from Fundus Images

Abstract: Retinal diseases (RD) are major causes of global vision impairment. Automated diagnosis using fundus images has significant clinical value, particularly in multi-label classification of RD.