Lung cancer remains a significant cause of mortality, with non-small cell lung cancer (NSCLC) representing most cases. Currently, clinical data based models fall short in predicting survival while more advanced deep learning based image models requir...
Developing selective kinase inhibitors is challenging due to the conserved kinase structures and costly kinome profiling experiments, highlighting the need for accurate prediction of kinase-inhibitor affinity and specificity. Here we present MMCLKin,...
INTRODUCTION: Post-intensive care syndrome affects up to 70% of adult intensive care unit (ICU) survivors, with ICU-acquired weakness contributing substantially to long-term disability. Despite evidence supporting early and structured rehabilitation ...
BACKGROUND: Reusing long-term data from electronic health records is essential for training reliable and effective health artificial intelligence (AI). However, intrinsic changes in health data distributions over time-known as dataset shifts, which i...
BACKGROUND: Addressing the complex medical and psychosocial needs of older adults is increasingly difficult in resource-limited care settings. In this context, socially assistive robots (SARs) provide support and practical functions such as orientati...
BACKGROUND: Digital tools that enable patients to submit information before consultations, such as Accurx and eConsult, are increasingly used in general practice. These systems aim to streamline workflows, improve documentation, and optimize consulta...
BACKGROUND: Large language models (LLMs) are increasingly used in medical education for feedback and grading; yet their role in postgraduate examination preparation remains uncertain due to inconsistent grading, hallucinations, and user acceptance.
PURPOSE: To evaluate and compare patient perceptions of artificial intelligence (AI) use in mammogram interpretation across academic and safety-net healthcare settings.
Microplastics transport toxins, disrupt microbial and nutrient cycles, bioaccumulate to cause oxidative stress and endocrine disruption, jeopardizing ecosystems and human health. Despite understanding microplastic origins, distribution, and microbial...
Agent-based modeling (ABM) is a powerful computational approach for studying complex biological and biomedical systems, yet its widespread use remains limited by significant computational demands. As models become increasingly sophisticated, the numb...
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