AIMC Topic: Clinical Decision-Making

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Effectiveness of Artificial Intelligence (AI) in Clinical Decision Support Systems and Care Delivery.

Journal of medical systems
This review aims to assess the effectiveness of AI-driven CDSSs on patient outcomes and clinical practices. A comprehensive search was conducted across PubMed, MEDLINE, and Scopus. Studies published from January 2018 to November 2023 were eligible fo...

Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...

Toward Realizing the Promise of AI in Precision Health Across the Spectrum of Care.

Annual review of genomics and human genetics
Significant progress has been made in augmenting clinical decision-making using artificial intelligence (AI) in the context of secondary and tertiary care at large academic medical centers. For such innovations to have an impact across the spectrum o...

Off-Label use of Woven EndoBridge device for intracranial brain aneurysm treatment: Modeling of occlusion outcome.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: The Woven EndoBridge (WEB) device is emerging as a novel therapy for intracranial aneurysms, but its use for off-label indications requires further study. Using machine learning, we aimed to develop predictive models for complete occlus...

Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.

Oncology
BACKGROUND: Clinical decision-making in oncology is a complex process influenced by numerous disease-related factors, patient demographics, and logistical considerations. With the advent of artificial intelligence (AI), precision medicine is undergoi...

Diagnostic accuracy of large language models in psychiatry.

Asian journal of psychiatry
INTRODUCTION: Medical decision-making is crucial for effective treatment, especially in psychiatry where diagnosis often relies on subjective patient reports and a lack of high-specificity symptoms. Artificial intelligence (AI), particularly Large La...

Trust criteria for artificial intelligence in health: normative and epistemic considerations.

Journal of medical ethics
Rapid advancements in artificial intelligence and machine learning (AI/ML) in healthcare raise pressing questions about how much users should trust AI/ML systems, particularly for high stakes clinical decision-making. Ensuring that user trust is prop...

Artificial intelligence in total and unicompartmental knee arthroplasty.

BMC musculoskeletal disorders
The application of Artificial intelligence (AI) and machine learning (ML) tools in total (TKA) and unicompartmental knee arthroplasty (UKA) emerges with the potential to improve patient-centered decision-making and outcome prediction in orthopedics, ...

Retrospective analysis of interpretable machine learning in predicting ICU thrombocytopenia in geriatric ICU patients.

Scientific reports
We developed an interpretable machine learning algorithm that prospectively predicts the risk of thrombocytopenia in older critically ill patients during their stay in the intensive care unit (ICU), ultimately aiding clinical decision-making and impr...