Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Feb 10, 2025
This study aims to construct a machine learning model to predict depression symptoms in the elderly and analyze the key influencing factors of depression in the elderly using the shapley additive interpretation (SHAP) method. Based on entries from ...
INTRODUCTION: Risk prediction models are increasingly used in healthcare to aid in clinical decision-making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for model develo...
BACKGROUND: Automatic landmarking software packages simplify the analysis of the 3D facial images. Their main deficiency is the limited accuracy of detecting landmarks for routine clinical applications. Cliniface is readily available open-access soft...
Cerebral cortex (New York, N.Y. : 1991)
Feb 5, 2025
Alzheimer's disease is an irreversible central neurodegenerative disease, and early diagnosis of Alzheimer's disease is beneficial for its prevention and early intervention treatment. In this study, we propose a novel framework, FusionNet-ISBOA-MK-SV...
SUMMARY: Polygenic risk scores (PRSs) hold promise for early disease diagnosis and personalized treatment, but their overall discriminative power remains limited for many diseases in the general population. As a result, numerous novel PRS modeling te...
MOTIVATION: Accurately identifying and predicting molecular properties is a crucial task in molecular machine learning, and the key lies in how to extract effective molecular representations. Contrastive learning opens new avenues for representation ...
MOTIVATION: Machine learning-based scoring functions (MLBSFs) have been found to exhibit inconsistent performance on different benchmarks and be prone to learning dataset bias. For the field to develop MLBSFs that learn a generalizable understanding ...
MOTIVATION: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models hav...
MOTIVATION: LLMs like GPT-4, despite their advancements, often produce hallucinations and struggle with integrating external knowledge effectively. While Retrieval-Augmented Generation (RAG) attempts to address this by incorporating external informat...
MOTIVATION: The drug-disease, gene-disease, and drug-gene relationships, as high-frequency edge types, describe complex biological processes within the biomedical knowledge graph. The structural patterns formed by these three edges are the graph moti...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.