AIMC Topic: Delivery of Health Care

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Decoding trust in large language models for healthcare in Saudi Arabia.

Scientific reports
This study investigates the factors influencing user trust and decision-making when using Artificial Intelligence (AI) systems, specifically focusing on ChatGPT in the healthcare domain within the Saudi context. As AI-powered conversational agents ar...

Optimizing healthcare supply chain capacity planning during disasters using fuzzy AHP and TOPSIS methods.

Scientific reports
This paper applies Fuzzy AHP and Fuzzy TOPSIS to the problem of healthcare supply-chain capacity planning under uncertainty. We define a practical set of criteria-patient demand, resource availability, cost, and quality of care and use fuzzy pairwise...

Unburdening Patients and Clinicians Through Automation and Artificial Intelligence: Informatics Strategies for Reducing Administrative Burden.

Journal of medical systems
Healthcare delivery systems face mounting administrative complexity that contributes to clinician burnout, medical errors, and reduced access to care for patients. This editorial explores how automation and artificial intelligence (AI) can address ke...

Energy-efficient clustering and routing for IoT-enabled healthcare using adaptive fuzzy logic and hybrid optimization.

Scientific reports
Leveraging Internet of Things technology in healthcare, including wireless sensor networks and next-generation networks, enhances the seamless integration of medical equipment and enables intelligent interaction among devices. This advancement plays ...

Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives.

European journal of medical research
Healthcare systems worldwide face growing challenges, including rising costs, workforce shortages, and disparities in access and quality, particularly in low- and middle-income countries. Artificial intelligence (AI) has emerged as a transformative t...

Maturity Framework for Operationalizing Machine Learning Applications in Health Care: Scoping Review.

Journal of medical Internet research
BACKGROUND: The exponential growth of publications regarding the application of machine learning (ML) tools in medicine highlights the significant potential for ML to revolutionize the field. Despite the multitude of literature surrounding this topic...

Capitalizing on Digital Health Care for Speech-Language Pathology and Audiology Professions to Be Contextually Relevant, Responsive, and Responsible in South Africa: A Narrative Review.

Journal of speech, language, and hearing research : JSLHR
BACKGROUND: The integration of digital health care technologies into speech-language pathology and audiology is rapidly transforming service delivery. In South Africa and other low- and middle-income countries (LMICs), digital tools offer significant...

Personalized health monitoring using explainable AI: bridging trust in predictive healthcare.

Scientific reports
AI has propelled the potential for moving toward personalized health and early prediction of diseases. Unfortunately, a significant limitation of many of these deep learning models is that they are not interpretable, restricting their clinical utilit...

Mapping interconnectivity of digital twin healthcare research themes through structural topic modeling.

Scientific reports
Digital twin (DT) technology is revolutionizing healthcare systems by leveraging real-time data integration and advanced analytics to enhance patient care, optimize clinical operations, and facilitate simulation. This study aimed to identify key rese...

Optimizing ensemble machine learning models for accurate liver disease prediction in healthcare.

PloS one
Liver disease encompasses a range of conditions affecting the liver, including hepatitis, cirrhosis, fatty liver, and liver cancer. It can be caused by infections, alcohol abuse, obesity, or genetic factors, and it often progresses silently until adv...