Artificial Intelligence Medical Compendium

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

Showing 11,741 to 11,750 of 210,187 articles

Learning From Crowds With Multiple Feature Dynamic Fusion-Based Annotation Generation.

IEEE transactions on pattern analysis and machine intelligence
As the scale of data grows for machine learning, annotating data accurately is extremely time-consuming and with high economic costs. To alleviate this dilemma, crowdsourcing has been widely used for data collection and annotation. Learning from crow... read more 

CTransFuse: A Hybrid Transformer-CNN Framework for Precise Meniscus Segmentation and Lesion Identification.

IEEE journal of biomedical and health informatics
Meniscal tears and degenerative changes are the most common pathologies affecting the knee joint. In magnetic resonance imaging (MRI), these lesions often manifest at small spatial scales with indistinct boundaries and heterogeneous intensity pattern... read more 

Consistency-based Semi-supervised Evidential Active Learning Framework for Robust Classification of Radiology Images.

IEEE journal of biomedical and health informatics
Deep learning offers high performance for radiology image classification, but relies on large, expert annotated datasets. Semi-supervised learning and active learning approaches can leverage unlabelled samples and mitigate the annotation burden. Comb... read more 

TwinRL-Onco: A World Model-Empowered Digital Twin Framework with Hierarchical Reinforcement Learning for Venetoclax Resistance Trajectory Prediction and Adaptive Therapy Optimization in Chronic Lymphocytic Leukemia.

IEEE journal of biomedical and health informatics
Chronic lymphocytic leukaemia (CLL) presents considerable therapeutic obstacles due to the development of treatment-resistant disease, especially with BCL-2 inhibitors like venetoclax, and is among the most challenging haematological malignancies to ... read more 

User-Guided Visual Analytics of Genome-wide DNA Methylation Data Based on Self-Organizing Maps.

IEEE transactions on computational biology and bioinformatics
DNA methylation is a key epigenetic modification with diagnostic and prognostic relevance across a wide range of diseases, particularly cancer. Modern array-based technologies enable high-throughput quantification of methylation states at hundreds of... read more 

BiasField: Interactive Bias Probing of Machine Learning Datasets.

IEEE transactions on visualization and computer graphics
Bias in machine learning datasets occurs when certain attributes are unfairly associated, e.g., serious males being mostly linked with law enforcement officers in job-related image datasets. Training models on biased datasets will degrade model perfo... read more 

Ethics and Fairness Considerations in AI-Based Deception Detection Technologies for Mental Health Applications: Focus Group Study.

JMIR AI
BACKGROUND: Artificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical documentation and decision-making. In parallel, AI-enabled deception detection, which leverages mult... read more 

AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study.

JMIR research protocols
BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfunction and fluctuating levels of consciousness. POD is associated with prolonged hospitalization, long-t... read more 

Sequencing AI Automation and Data Interoperability in Oncology Using a Scenario-Planning Framework Coupled With Discrete-Event Simulation: Proof-of-Concept Study.

Journal of medical Internet research
BACKGROUND: As oncology workflows integrate increasingly autonomous artificial intelligence (AI) agents, health systems face uncertainty regarding operational impacts. Traditional linear forecasting methods fail to capture second-order effects such a... read more 

Patients' Perspectives on the Implementation of AI in Radiological Diagnostics: Focus Group Study.

Journal of medical Internet research
BACKGROUND: Rapid developments in artificial intelligence (AI) will enable its widespread use in radiological diagnostics in the near future. Patients will then be confronted with findings generated with the help of AI. Understanding patients' perspe... read more