IEEE transactions on pattern analysis and machine intelligence
May 25, 2026
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
IEEE journal of biomedical and health informatics
May 25, 2026
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
IEEE journal of biomedical and health informatics
May 25, 2026
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
IEEE journal of biomedical and health informatics
May 25, 2026
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
IEEE transactions on computational biology and bioinformatics
May 25, 2026
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
IEEE transactions on visualization and computer graphics
May 25, 2026
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
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
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
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
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
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