AIMC Topic: Decision Support Systems, Clinical

Clear Filters Showing 161 to 170 of 811 articles

Evaluating Explanations From AI Algorithms for Clinical Decision-Making: A Social Science-Based Approach.

IEEE journal of biomedical and health informatics
Explainable Artificial Intelligence (XAI) techniques generate explanations for predictions from AI models. These explanations can be evaluated for (i) faithfulness to the prediction, i.e., its correctness about the reasons for prediction, and (ii) us...

Comparing performance of primary care clinicians in the interpretation of SPIROmetry with or without Artificial Intelligence Decision support software (SPIRO-AID): a protocol for a randomised controlled trial.

BMJ open
INTRODUCTION: Spirometry is a point-of-care lung function test that helps support the diagnosis and monitoring of chronic lung disease. The quality and interpretation accuracy of spirometry is variable in primary care. This study aims to evaluate whe...

Doctors' perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore.

Frontiers in public health
OBJECTIVES: The increased utilization of Artificial intelligence (AI) in healthcare changes practice and introduces ethical implications for AI adoption in medicine. We assess medical doctors' ethical stance in situations that arise in adopting an AI...

Medical-informed machine learning: integrating prior knowledge into medical decision systems.

BMC medical informatics and decision making
BACKGROUND: Clinical medicine offers a promising arena for applying Machine Learning (ML) models. However, despite numerous studies employing ML in medical data analysis, only a fraction have impacted clinical care. This article underscores the impor...

Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support.

Journal of medical Internet research
Artificial intelligence (AI)-based clinical decision support systems are gaining momentum by relying on a greater volume and variety of secondary use data. However, the uncertainty, variability, and biases in real-world data environments still pose s...

TransKinect: a computer vision and machine learning clinical decision support system for automatic independent wheelchair transfer technique assessment.

Disability and rehabilitation. Assistive technology
BACKGROUND: Physical and occupational therapists provide routine care for manual wheelchair users and are responsible for training and assessing the quality of transfers. These transfers can produce large loads on the upper extremity joints if improp...

Optimal use of β-lactams in neonates: machine learning-based clinical decision support system.

EBioMedicine
BACKGROUND: Accurate prediction of the optimal dose for β-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliable clinical decision support system (CDSS) based on machine learning (ML) can assist clinicians in ma...

Constructing and implementing a performance evaluation indicator set for artificial intelligence decision support systems in pediatric outpatient clinics: an observational study.

Scientific reports
Artificial intelligence (AI) decision support systems in pediatric healthcare have a complex application background. As an AI decision support system (AI-DSS) can be costly, once applied, it is crucial to focus on its performance, interpret its succe...

Improving clinical abbreviation sense disambiguation using attention-based Bi-LSTM and hybrid balancing techniques in imbalanced datasets.

Journal of evaluation in clinical practice
RATIONALE: Clinical abbreviations pose a challenge for clinical decision support systems due to their ambiguity. Additionally, clinical datasets often suffer from class imbalance, hindering the classification of such data. This imbalance leads to cla...