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Decision Support Systems, Clinical

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User-Centered Methods in Explainable AI Development for Hospital Clinical Decision Support: A Scoping Review.

Studies in health technology and informatics
Explainable Artificial Intelligence (XAI) offers promising advancements in enhancing transparency and usability of AI-based Clinical Decision Support Systems (CDSS) in healthcare settings. These tools aim to improve clinical outcomes by assisting wit...

Knowledge Uncertainty Estimation for Reliable Clinical Decision Support: A Delirium Risk Prognosis Case Study.

Studies in health technology and informatics
INTRODUCTION: Predictive models hold significant potential in healthcare, but their adoption in clinical settings is hampered by limited trust due to their inability to recognize when presented with unfamiliar data. Estimating knowledge uncertainty (...

Integrating Artificial Intelligence (AI) With Workforce Solutions for Sustainable Care: A Follow Up to Artificial Intelligence and Machine Learning (ML) Based Decision Support Systems in Mental Health.

International journal of mental health nursing
This integrative literature review examines the evolving role of artificial intelligence (AI) and machine learning (ML) based clinical decision support systems (CDSS) in mental health (MH) care, expanding on findings from a prior review (Higgins et a...

Do explainable AI (XAI) methods improve the acceptance of AI in clinical practice? An evaluation of XAI methods on Gleason grading.

The journal of pathology. Clinical research
This work aimed to evaluate both the usefulness and user acceptance of five gradient-based explainable artificial intelligence (XAI) methods in the use case of a prostate carcinoma clinical decision support system environment. In addition, we aimed t...

A Guide for Implementing an A.I-Driven Initiative in Rural Northern Ontario.

Studies in health technology and informatics
Diagnosing pulmonary embolism (PE) often requires specialized expertise in interpreting x-rays and radiographic images, resources that are mostly limited in rural settings. This paper explores the development of an electronic health record (EHR) syst...

Using human factors methods to mitigate bias in artificial intelligence-based clinical decision support.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To highlight the often overlooked role of user interface (UI) design in mitigating bias in artificial intelligence (AI)-based clinical decision support (CDS).

Advancements of AI in healthcare: a comprehensive review of ChatGPT's applications and challenges.

JPMA. The Journal of the Pakistan Medical Association
The rapid integration of artificial intelligence into healthcare has introduced transformative possibilities and challenges. The current narrative review was planned to explore diverse applications of Chat Generative Pre-Trained Transformer (ChatGPT)...

A Visual Analytics Framework for Assessing Interactive AI for Clinical Decision Support.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Human involvement remains critical in most instances of clinical decision-making. Recent advances in AI and machine learning opened the door for designing, implementing, and translating interactive AI systems to support clinicians in decision-making....

Computerized Decision Support System and Fuzzy Logic Rules for Early Diagnosis of Pesticide-Induced Diseases.

Critical reviews in biomedical engineering
Many reflexologists employ outdated concepts that do not align with modern anatomy, physiology, and biophysics. Those concepts undermine physicians' confidence in their diagnosis. This study aims to improve the quality of medical care for workers in ...