An overview of clinical decision support systems: benefits, risks, and strategies for success

RT Sutton, D Pincock, DC Baumgart… - NPJ digital …, 2020 - nature.com
Computerized clinical decision support systems, or CDSS, represent a paradigm shift in
healthcare today. CDSS are used to augment clinicians in their complex decision-making …

The role of artificial intelligence in improving patient outcomes and future of healthcare delivery in cardiology: a narrative review of the literature

D Gala, H Behl, M Shah, AN Makaryus - Healthcare, 2024 - mdpi.com
Cardiovascular diseases exert a significant burden on the healthcare system worldwide.
This narrative literature review discusses the role of artificial intelligence (AI) in the field of …

[HTML][HTML] Patient satisfaction and trust in telemedicine during the COVID-19 pandemic: retrospective observational study

S Orrange, A Patel, WJ Mack… - JMIR human factors, 2021 - humanfactors.jmir.org
Background Los Angeles County is a hub for COVID-19 cases in the United States.
Academic health centers rapidly deployed and leveraged telemedicine to permit …

Human-centered tools for co** with imperfect algorithms during medical decision-making

CJ Cai, E Reif, N Hegde, J Hipp, B Kim… - Proceedings of the …, 2019 - dl.acm.org
Machine learning (ML) is increasingly being used in image retrieval systems for medical
decision making. One application of ML is to retrieve visually similar medical images from …

Challenges and opportunities beyond structured data in analysis of electronic health records

M Tayefi, P Ngo, T Chomutare… - Wiley …, 2021 - Wiley Online Library
Electronic health records (EHR) contain a lot of valuable information about individual
patients and the whole population. Besides structured data, unstructured data in EHRs can …

“Brilliant AI doctor” in rural clinics: challenges in AI-powered clinical decision support system deployment

D Wang, L Wang, Z Zhang, D Wang, H Zhu… - Proceedings of the …, 2021 - dl.acm.org
Artificial intelligence (AI) technology has been increasingly used in the implementation of
advanced Clinical Decision Support Systems (CDSS). Research demonstrated the potential …

Designing AI for trust and collaboration in time-constrained medical decisions: a sociotechnical lens

M Jacobs, J He, M F. Pradier, B Lam, AC Ahn… - Proceedings of the …, 2021 - dl.acm.org
Major depressive disorder is a debilitating disease affecting 264 million people worldwide.
While many antidepressant medications are available, few clinical guidelines support …

Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges

S El-Sappagh, JM Alonso-Moral, T Abuhmed… - Artificial Intelligence …, 2023 - Springer
Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …

[HTML][HTML] Clinical decision support models and frameworks: seeking to address research issues underlying implementation successes and failures

RA Greenes, DW Bates, K Kawamoto… - Journal of biomedical …, 2018 - Elsevier
Computer-based clinical decision support (CDS) has been pursued for more than five
decades. Despite notable accomplishments and successes, wide adoption and broad use of …

Introduction of human-centric AI assistant to aid radiologists for multimodal breast image classification

FM Calisto, C Santiago, N Nunes… - International Journal of …, 2021 - Elsevier
In this research, we take an HCI perspective on the opportunities provided by AI techniques
in medical imaging, focusing on workflow efficiency and quality, preventing errors and …