Results 111 to 120 of about 52,853 (237)

Modeling the Construct of an Expert Evidence-Adaptive Knowledge Base for a Pressure Injury Clinical Decision Support System

Informatics, 2017
The selection of appropriate wound products for the treatment of pressure injuries is paramount in promoting wound healing. However, nurses find it difficult to decide on the most optimal wound product(s) due to limited live experiences in managing ...
Peck Chui Betty Khong, Leng Noey Lee, Apolino Ilagan Dawang   +2 more
doaj   +1 more source

An Advanced Machine Learning Model for a Web-Based Artificial Intelligence–Based Clinical Decision Support System Application: Model Development and Validation Study

Journal of Medical Internet Research
Background Breast cancer is a leading global health concern, necessitating advancements in recurrence prediction and management. The development of an artificial intelligence (AI)–based clinical decision support system (AI-CDSS) using ChatGPT addresses ...
Tai-Han Lin, Hsing-Yi Chung, M. Jian, Chih-Kai Chang, C. Perng, G. Liao, Jyh-Cherng Yu, Ming-Shen Dai, Cheng-Ping Yu, Hung-Sheng Shang   +9 more
semanticscholar   +1 more source

Effects of computerised clinical decision support systems (CDSS) on nursing and allied health professional performance and patient outcomes: a systematic review of experimental and observational studies [PDF]

, 2021
Teumzghi F Mebrahtu, Sarah Skyrme, Rebecca Randell, Anne‐Maree Keenan, Karen Bloor, Huiqin Yang, Deirdre Andre, Alison Ledward, Henry King, Carl Thompson   +9 more
openalex   +1 more source

An AI-Based Clinical Decision Support System for Antibiotic Therapy in Sepsis (KINBIOTICS): Use Case Analysis

JMIR Human Factors
Background Antimicrobial resistances pose significant challenges in health care systems. Clinical decision support systems (CDSSs) represent a potential strategy for promoting a more targeted and guideline-based use of antibiotics.
J. Düvel, David Lampe, Maren Kirchner, S. Elkenkamp, Philipp Cimiano, Christoph Düsing, H. Marchi, S. Schmiegel, Christian J Fuchs, Simon Claßen, K. Meier, Rainer Borgstedt, Sebastian Rehberg, W. Greiner   +13 more
semanticscholar   +1 more source

Challenges and insights from implementing clinical decision support systems for radiologic imaging: experience from the MIDAS trial

Insights into Imaging
Clinical decision support systems (CDSSs) have been developed to give guidance for referring physicians to make appropriate decisions at the point of care.
Thomas Kroencke, Stijntje W. Dijk, Moritz C. Halfmann, Claudia Wollny, Joerg Barkhausen, Olav Janssen, Dimitris Rizopoulos, M. G. Myriam Hunink   +7 more
doaj   +1 more source

Considerations about Developing A Clinical Decision Support System for Evidence-based Diagnosis and Treatment of Acupuncture-moxibustion

针刺研究, 2009
To develop a practical clinical decision support system(CDSS) for acu-moxibustion therapy is of highly realistic significance in assisting acupuncturists with their decision-making tasks.In the present paper,the authors review the general state of ...
REN Yu-lan, ZENG Fang1, ZHAO Ling1, YANG Jie1, LIANG Fan-rong1   +4 more
doaj  

Developing an AI-assisted clinical decision support system to enhance in-patient holistic health care

PLoS ONE, 2022
Holistic health care (HHC) is a synonym for complete patient care, and as such an efficient clinical decision support system (CDSS) for HHC is critical to support the judgement of physician’s decision in response of patient’s physical, emotional, social,
Wang-Chuan Juang, Ming-Hsia Hsu, Zheng-Xun Cai, Chia-Mei Chen   +3 more
doaj  

Developing public health clinical decision support systems (CDSS) for the outpatient community in New York City: our experience [PDF]

, 2011
Sam Amirfar, John Taverna, Sheila Anane, Jesse Singer   +3 more
openalex   +1 more source

Design electronic medical records with clinical decision support system (CDSS) to prevent interaction of drug content in outpatient department

, 2022
Feby Erawantini, Sustin Farlinda, Arinda Lironika Suryana   +2 more
openalex   +2 more sources

AXAI-CDSS: An Affective Explainable AI-Driven Clinical Decision Support System for Cannabis Use

2025 International Conference on Activity and Behavior Computing (ABC)
As cannabis use has increased in recent years, researchers have come to rely on sophisticated machine learning models to predict cannabis use behavior and its impact on health. However, many artificial intelligence (AI) models lack transparency and interpretability due to their opaque nature, limiting their trust and adoption in real-world medical ...
Tongze Zhang, Tammy Chung, Anind K. Dey, Sangwon Bae 0001   +3 more
openaire   +2 more sources