paperarXivTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy
Medical Artificial Intelligence (AI) is widely expected to transform clinical practice, yet the decision-making processes of many Machine Learning (ML) models remain opaque. Explainability has been advanced as a partial remedy to clarify why AI generates predictions, particularly in high-stakes contexts. Despite ongoing efforts, debates on what constitutes an adequate medical explanation remain unsettled. Yet, explanation has long been a central topic of inquiry in the philosophy of science and medicine. The insights developed in these fields, however, have been largely overlooked in contempor
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- LinkedLinked via unknownUsing AI to help physicians diagnose rare genetic diseases affecting children →
- LinkedLinked via unknownEmpowering biomedical evidence exploration and synthesis with deep knowledge graph research →
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- PossiblePossibly related (embedding) · 49%Most nurses say AI isn’t good enough to trust with patient care, survey finds - The Washington Post →
- PossiblePossibly related (embedding) · 46%Dependence on Generative Artificial Intelligence Among Medical Students and Its Association With Critical Thinking: A Cross-Sectional Study - Cureus →
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newsEmpowering biomedical evidence exploration and synthesis with deep knowledge graph researchnewsMachine learning boosts medicine access in resource-limited healthcare settings - News-MedicalnewsAI Is Accelerating Drug Discovery, but Patients Will Prove Its True Value - Technology NetworksnewsThe Evolution of Artificial Intelligence in Oncology: Impact on Trials, Workflows, and Outcomes - CancerNetworknewsAI Analysis of Perioperative Data Improves Prediction of Postoperative Complications - OR Management NewsnewsMost nurses say AI isn’t good enough to trust with patient care, survey finds - The Washington PostnewsDependence on Generative Artificial Intelligence Among Medical Students and Its Association With Critical Thinking: A Cross-Sectional Study - CureusnewsOIG Report: VA’s Aggressive Deployment of AI in the Clinical Field Considered ‘Risky’ - U.S. MedicinenewsThree Decades of Food and Drug Administration Authorizations of Artificial Intelligence/Machine Learning-Enabled Medical Devices: Persistent Specialty Concentration and the Care-Delivery Gap (1995–2025) - CureusnewsPatient-Reported Outcomes, Machine Learning May Predict Breast Cancer Recurrence Earlier - Pharmacy TimesnewsArtificial Intelligence in Cardiology: Applications in Diagnosis and Risk Prediction - CureusnewsArtificial Intelligence in Pharmacy Practice: Enhancing Efficiency and Clinical Decision-Making - Pharmacy TimesnewsAI toxicity prediction: What machine learning models can (and can't) tell you about drug safety - Drug Discovery NewsnewsReal-Time Artificial Intelligence for Early Sepsis Prediction Using Dynamic Clinical Data: A Systematic Review - CureusnewsArtificial Intelligence in Predicting Systemic Complications From Retinal Findings: A New Frontier in Precision Medicine - Cureus
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newsArtificial Intelligence in Cardiology: Applications in Diagnosis and Risk Prediction - CureusnewsReal-Time Artificial Intelligence for Early Sepsis Prediction Using Dynamic Clinical Data: A Systematic Review - CureusnewsThree Decades of Food and Drug Administration Authorizations of Artificial Intelligence/Machine Learning-Enabled Medical Devices: Persistent Specialty Concentration and the Care-Delivery Gap (1995–2025) - CureusnewsAI toxicity prediction: What machine learning models can (and can't) tell you about drug safety - Drug Discovery NewsnewsAI Is Accelerating Drug Discovery, but Patients Will Prove Its True Value - Technology NetworksrepoexplainX/explainxnewsEmpowering biomedical evidence exploration and synthesis with deep knowledge graph researchnewsUsing AI to help physicians diagnose rare genetic diseases affecting childrennewsThe Evolution of Artificial Intelligence in Oncology: Impact on Trials, Workflows, and Outcomes - CancerNetworknewsAI Analysis of Perioperative Data Improves Prediction of Postoperative Complications - OR Management NewsnewsOIG Report: VA’s Aggressive Deployment of AI in the Clinical Field Considered ‘Risky’ - U.S. MedicinenewsMachine learning boosts medicine access in resource-limited healthcare settings - News-MedicalnewsDependence on Generative Artificial Intelligence Among Medical Students and Its Association With Critical Thinking: A Cross-Sectional Study - CureusnewsArtificial Intelligence in Predicting Systemic Complications From Retinal Findings: A New Frontier in Precision Medicine - CureusnewsArtificial Intelligence in Pharmacy Practice: Enhancing Efficiency and Clinical Decision-Making - Pharmacy TimesnewsMost nurses say AI isn’t good enough to trust with patient care, survey finds - The Washington PostnewsPatient-Reported Outcomes, Machine Learning May Predict Breast Cancer Recurrence Earlier - Pharmacy Times