Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 62,661 to 62,670 of 230,507 articles

Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers.

Physiological measurement
Objective.Large vessel occlusion (LVO) stroke presents a major challenge in clinical practice due to the potential for poor outcomes with delayed treatment. Treatment for LVO involves highly specialized care, in particular endovascular thrombectomy, ... read more 

Validation of uPath HER2 dual-colour dual in-situ hybridisation image analysis tool for HER2/neu testing in breast cancer.

Journal of clinical pathology
AIMS: HER2/neu gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical prognostic and predictive marker. HER2-targeted therapies have improved outcomes for HER2-positive patients, highlighting the importance of accurate as... read more 

Machine learning-enabled metabolomics for geographical authentication of Lonicera japonica via UHPLC-Q-TOF-MS/MS and SHAP interpretation.

Food chemistry
Geographical traceability is vital for ensuring the authenticity and quality of food and medicinal plants. Lonicera japonica Thunb. (Jinyinhua, JYH) is widely consumed for its pharmacological and nutritional benefits, yet its quality is strongly orig... read more 

Learning frequency-aware graph fraud detection.

Neural networks : the official journal of the International Neural Network Society
Graph Fraud Detection (GFD) has become a critical task in online systems such as financial networks, review platforms, and social media, where fraudulent behaviors are inherently rare and often embedded within benign communities. Graph Neural Network... read more 

GIN-transformer based pairwise graph contrastive learning framework.

Neural networks : the official journal of the International Neural Network Society
Resting-state functional magnetic resonance imaging (rs-fMRI) provides critical biomarkers for diagnosing neuropsychiatric disorders such as autism spectrum disorder (ASD) and major depressive disorder (MDD). However, existing deep learning models he... read more 

Global inland waters trophic status from space observation: scientific advances and future challenges.

Water research
Inland waters represent a significant share of the global freshwater resources and can have a profound impact on global climate and human well-being. By 2050, the world's population is expected to reach 9.7 billion, and one in four people is expected... read more 

Avocado ripeness classification using handheld Raman spectroscopy: addressing data imbalance with machine learning and resampling techniques.

Food chemistry
Food waste is a global concern, partially caused by destructive testing and inaccurate visual inspections that misclassify quality. This study developed a machine learning-assisted handheld Raman spectroscopy for non-destructive classification of avo... read more 

Interpretable machine learning model for predicting in-hospital mortality in elderly acute pancreatitis: Development and validation in a multicenter cohort.

International journal of medical informatics
BACKGROUND: Elderly acute pancreatitis (AP) patients face significantly higher in-hospital all-cause mortality, highlighting the need for effective risk stratification to support timely clinical decision-making. METHODS: We conducted a multicenter re... read more 

Integrating artificial intelligence to enhance inclusive education for students with special needs in Jordan and the UAE: Perspectives of teachers and parents.

Acta psychologica
This study examines the potential of integrating artificial intelligence (AI) into inclusive education practices in Jordan and the UAE, focusing on the perceptions of teachers and parents regarding its role in promoting inclusive classrooms. A mixed-... read more 

Deformable Point Cloud Registration-Based Bidirectional Local Distance (DPCR-BLD): A Methodology for Systematic Evaluation and Visualization of Local Disagreements in Clinical Autocontouring.

International journal of radiation oncology, biology, physics
PURPOSE: Variability in autosegmentation can arise from the training data, leading to disagreements with clinical practice. The anisotropic and localized nature of disagreements between 2 contours makes them challenging to evaluate using common metri... read more