AIMC Topic: Risk Assessment
Clear Filters Showing 141 to 150 of 2719 articles
A plasma metabolome-derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank.
Diabetes, obesity & metabolism
Jun 11, 2025
AIMS: Severe liver disease (SLD) in nonalcoholic fatty liver disease (NAFLD) is often diagnosed late due to the long asymptomatic period of progressive fibrosis. We aimed to identify metabolomic profiles associated with SLD and develop a predictive m...
Identification of neurological text markers associated with risk of stroke.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jun 11, 2025
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...
Data Mining
Academic Medical Centers
Predictive Value of Tests
Natural Language Processing
Emergency Service, Hospital
Stroke
Reproducibility of Results
Risk Factors
Aged
Aged, 80 and over
Male
Middle Aged
Risk Assessment
Time Factors
Prognosis
Retrospective Studies
Electronic Health Records
Female
Humans
Explainable machine learning model for predicting internal mammary node metastasis in breast cancer: Multi-method development and cross-cohort validation.
Breast (Edinburgh, Scotland)
Jun 9, 2025
BACKGROUND: This study developed an explainable machine learning model for baseline internal mammary lymph node metastasis (IMNM) in breast cancer patients.
QSAR Model Development for the Environmental Risk Limits and High-Risk List Identification of Phenylurea Herbicides in Aquatic Environments.
Journal of agricultural and food chemistry
Jun 9, 2025
Due to the extensive residues of phenylurea herbicides (PUHs) in the environment, it is important for the ecological risk assessment of PUHs to determine their environmental risk limits and identify the high-risk PUHs. This study derived the environm...
Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease.
Italian journal of pediatrics
Jun 9, 2025
BACKGROUND: Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10-20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. E...
Diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors: A systematic review and meta-analysis.
European journal of radiology
Jun 7, 2025
RATIONALE AND OBJECTIVES: This systematic review and meta-analysis aimed to assess the diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors (GISTs). It focused on evaluating radiomic models as a non-invasive tool...
Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.
BMC medical informatics and decision making
Jun 6, 2025
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset from the ...
Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.
BMJ health & care informatics
Jun 6, 2025
OBJECTIVES: Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). Distinguishing true NSTE-ACS from non-cardiac chest pain based solely on the EC...
Preliminary analysis of AI-based thyroid nodule evaluation in a non-subspecialist endocrinology setting.
Endocrine
Jun 5, 2025
PURPOSE: Thyroid nodules are commonly evaluated using ultrasound-based risk stratification systems, which rely on subjective descriptors. Artificial intelligence (AI) may improve assessment, but its effectiveness in non-subspecialist settings is uncl...
Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China.
Ecotoxicology and environmental safety
Jun 5, 2025
Soil heavy metal contamination poses serious health risks, but few studies have quantitatively assessed disparities in these risks between urban and rural populations. To address this gap, we introduce a novel framework integrating machine learning a...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32510
- Neural Networks, Computer 30481
- Algorithms 27731
- Deep Learning 27277
- Artificial Intelligence 25203
- Robotics 13428
- Image Processing, Computer-Assisted 9883
- Retrospective Studies 9527
- Magnetic Resonance Imaging 6481
- Reproducibility of Results 5744
- Tomography, X-Ray Computed 4956
- Support Vector Machine 4812
- Computational Biology 4392
- Brain 4186
- Computer Simulation 3962
Recent Journals
- Scientific reports 7009
- Sensors (Basel, Switzerland) 4794
- PloS one 4295
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2037
- Computational intelligence and neuroscience 1931
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1395
- IEEE journal of biomedical and health informatics 1191
- Journal of chemical information and modeling 1083
- Nature communications 1070
- Computer methods and programs in biomedicine 895
- Bioinformatics (Oxford, England) 879
- Journal of medical Internet research 878
- IEEE transactions on neural networks and learning systems 859