Despite advances in precision oncology, clinical decision-making still relies on limited variables and expert knowledge. To address this limitation, we combined multimodal real-world data and explainable artificial intelligence (xAI) to introduce AI-...
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics...
BACKGROUND: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variati...
With the emergence of numerous classifications, surgical treatment for adolescent idiopathic scoliosis (AIS) can be guided more effectively. However, surgical decision-making and optimal strategies still lack standardization and personalized customiz...
American journal of obstetrics & gynecology MFM
Jan 23, 2025
OBJECTIVE: Machine learning (ML), a subtype of artificial intelligence (AI), presents predictive modeling and dynamic diagnostic tools to facilitate early interventions and improve decision-making. Considering the global challenges of maternal, fetal...
Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics
Jan 23, 2025
Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Characteristic EEG changes have been identified in diverse neurologic conditions including stroke, trauma, and anoxia, and the increased utilization of co...
INTRODUCTION: Artificial intelligence (AI) allows the optimization of diagnostic processes for hepatitis C virus (HCV) patients. Our objective was to evaluate the clinical, economic, and management benefits of an AI-based clinical decision support sy...
The development of new therapeutic strategies such as immune checkpoint inhibitors (ICIs) and targeted therapies has increased the complexity of the treatment landscape for solid tumors. At the current rate of annual FDA approvals, the potential trea...
Clinical decision-making is driven by multimodal data, including clinical notes and pathological characteristics. Artificial intelligence approaches that can effectively integrate multimodal data hold significant promise in advancing clinical care. H...
BACKGROUND: Patients with heart failure frequently face the possibility of rehospitalization following an initial hospital stay, placing a significant burden on both patients and health care systems. Accurate predictive tools are crucial for guiding ...
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