Results 61 to 70 of about 52,853 (237)

The Effects of Implementing Clinical Decision Support Systems on the Diagnosis, Treatment and Management of Cancers: A Systematic Review

پیاورد سلامت, 2022
Background and Aim: Cancer is the second leading cause of death in the world, which leads to the death of more than 10 million people in the world every year.
saman Mohammadpour, Reza Rabiei, Elham Shabahrami, Kamyar Fathisalari, Maryam Khakzad, Mostafa Langarizadeh   +5 more
doaj  

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

To explain or not to explain?-Artificial intelligence explainability in clinical decision support systems.

PLOS Digital Health, 2022
Explainability for artificial intelligence (AI) in medicine is a hotly debated topic. Our paper presents a review of the key arguments in favor and against explainability for AI-powered Clinical Decision Support System (CDSS) applied to a concrete use ...
Julia Amann, Dennis Vetter, Stig Nikolaj Blomberg, Helle Collatz Christensen, Megan Coffee, Sara Gerke, Thomas K Gilbert, Thilo Hagendorff, Sune Holm, Michelle Livne, Andy Spezzatti, Inga Strümke, Roberto V Zicari, Vince Istvan Madai, Z-Inspection initiative   +14 more
doaj   +2 more sources

Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital

BMC Medical Informatics and Decision Making, 2023
Background Natural language processing (NLP) based clinical decision support systems (CDSSs) have demonstrated the ability to extract vital information from patient electronic health records (EHRs) to facilitate important decision support tasks.
G. T. Berge, Ole-Christoffer Granmo, T. Tveit, B. Munkvold, A. L. Ruthjersen, J. Sharma   +5 more
semanticscholar   +1 more source

Applying Change Models and Methods During a Period of Vast Digital Transformation: A Systematic Review of Practice in Healthcare

The International Journal of Health Planning and Management, EarlyView.
ABSTRACT Introduction Reflection and learning about the use of virtual care in healthcare delivery has become a central goal for health systems internationally. Insights drawn in the aftermath of the COVID‐19 pandemic have led to vast changes to embed virtual care in health care delivery. This study explored the methodologies used to manage change that
Rebecca McDonnell, Ashfaq Chauhan, Corey Adams, Alexander Cardenas, Michelle Moscova, Ramya Walsan, Maryam Sina, Alice Munro, Elizabeth Manias, Rebecca Mitchell, Anthony Gust, Sabe Sabesan, Reema Harrison   +12 more
wiley   +1 more source

Computerised clinical decision support system for the diagnosis of pulmonary thromboembolism: a preclinical pilot study

BMJ Open Quality, 2023
Background Recommendations for the diagnosis of pulmonary embolism are available for healthcare providers. Yet, real practice data show existing gaps in the translation of evidence-based recommendations.
William A Ghali, Brenda Hemmelgarn, Ward Flemons, Kevin McLaughlin, Ghazwan Altabbaa, Sheelagh Carpendale, Torre Zuk   +6 more
doaj   +1 more source

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus

Scientific Reports, 2022
Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity.
Yuhan Du, Anthony R. Rafferty, F. Mcauliffe, Lan Wei, C. Mooney   +4 more
semanticscholar   +1 more source

Microbial keystone taxa and metabolic signatures in centenarians regulate intestinal homeostasis during aging

iMeta, EarlyView.
Clostridium scindens and its metabolite indole‐3‐acetic acid (IAA) are identified as a keystone taxon and metabolic signature in centenarians. Clostridium scindens enhances microbial network stability and produces IAA via its own amidase (AMIE) and aldehyde dehydrogenase (ALDH), thus promoting intestinal homeostasis by activating the aryl hydrocarbon ...
Wei‐Chuan Lin, Cui Zhang, He‐Hua Lei, Zheng Cao, Xin Gao, Wen‐Kai Yu, Xin‐Zhi Li, Qing‐Wei Xiang, Zhi‐Wen Zhang, Shi‐Fu Pang, Wei‐Fei Luo, Deng‐Hui Xie, Li‐Min Zhang, Gang Chen   +13 more
wiley   +1 more source

Startups Driving Artificial Intelligence Into Clinical Dermatology

JEADV Clinical Practice, EarlyView.
ABSTRACT Artificial intelligence (AI) is rapidly transitioning from innovation to routine clinical application in dermatology. This review examines how AI‐enabled technologies are being developed and integrated across diverse clinical purposes and workflows.
Dominique Du Crest, Benjamin Miguel Monteagudo, Stanislas Vandier, Mullarkey Dan, Svedenhag Per, Jon Friis, Monisha Madhumita, Lilit Garibyan, Tu‐Anh Duong, Merete Haedersdal, Vinzent Kevin Ortner   +10 more
wiley   +1 more source

An AI-Powered Clinical Decision Support System to Predict Flares in Rheumatoid Arthritis: A Pilot Study

Diagnostics, 2023
Treat-to-target (T2T) is a main therapeutic strategy in rheumatology; however, patients and rheumatologists currently have little support in making the best treatment decision. Clinical decision support systems (CDSSs) could offer this support.
H. Labinsky, D. Ukalovic, F. Hartmann, Vanessa Runft, André Wichmann, Jan Jakubcik, Kira Gambel, K. Otani, H. Morf, J. Taubmann, F. Fagni, A. Kleyer, D. Simon, G. Schett, M. Reichert, J. Knitza   +15 more
semanticscholar   +1 more source