AIMC Topic: Decision Support Systems, Clinical
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A pre-trained language model for emergency department intervention prediction using routine physiological data and clinical narratives.
International journal of medical informatics
Aug 3, 2024
INTRODUCTION: The urgency and complexity of emergency room (ER) settings require precise and swift decision-making processes for patient care. Ensuring the timely execution of critical examinations and interventions is vital for reducing diagnostic e...
The Impact of Information Relevancy and Interactivity on Intensivists' Trust in a Machine Learning-Based Bacteremia Prediction System: Simulation Study.
JMIR human factors
Aug 1, 2024
BACKGROUND: The exponential growth in computing power and the increasing digitization of information have substantially advanced the machine learning (ML) research field. However, ML algorithms are often considered "black boxes," and this fosters dis...
Making Co-Design More Responsible: Case Study on the Development of an AI-Based Decision Support System in Dementia Care.
JMIR human factors
Jul 31, 2024
BACKGROUND: Emerging technologies such as artificial intelligence (AI) require an early-stage assessment of potential societal and ethical implications to increase their acceptability, desirability, and sustainability. This paper explores and compare...
Rare disease diagnosis using knowledge guided retrieval augmentation for ChatGPT.
Journal of biomedical informatics
Jul 29, 2024
Although rare diseases individually have a low prevalence, they collectively affect nearly 400 million individuals around the world. On average, it takes five years for an accurate rare disease diagnosis, but many patients remain undiagnosed or misdi...
A decision support system for the detection of cutaneous fungal infections using artificial intelligence.
Pathology, research and practice
Jul 21, 2024
Cutaneous fungal infections are one of the most common skin conditions, hence, the burden of determining fungal elements upon microscopic examination with periodic acid-Schiff (PAS) and Gomori methenamine silver (GMS) stains, is very time consuming. ...
MoCab: A framework for the deployment of machine learning models across health information systems.
Computer methods and programs in biomedicine
Jul 20, 2024
BACKGROUND AND OBJECTIVE: Machine learning models are vital for enhancing healthcare services. However, integrating them into health information systems (HISs) introduces challenges beyond clinical decision making, such as interoperability and divers...
Development, validation, and usability evaluation of machine learning algorithms for predicting personalized red blood cell demand among thoracic surgery patients.
International journal of medical informatics
Jul 18, 2024
INTRODUCTION: Preparing appropriate red blood cells (RBCs) before surgery is crucial for improving both the efficacy of perioperative workflow and patient safety. In particular, thoracic surgery (TS) is a procedure that requires massive transfusion w...
[Supporting medical and nursing activities with AI: recommendations for responsible design and use].
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Jul 17, 2024
Clinical decision support systems (CDSS) based on artificial intelligence (AI) are complex socio-technical innovations and are increasingly being used in medicine and nursing to improve the overall quality and efficiency of care, while also addressin...
Artificial intelligence in colorectal multidisciplinary team meetings. What are the medicolegal implications?
Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
Jul 16, 2024
AIM: To give an insight into areas for future development and suggestions in the complexities of incorporation of AI into human colorectal cancer (CRC) care while bringing into focus the importance of clinicians' roles in patient care.
Towards multimodal graph neural networks for surgical instrument anticipation.
International journal of computer assisted radiology and surgery
Jul 10, 2024
PURPOSE: Decision support systems and context-aware assistance in the operating room have emerged as the key clinical applications supporting surgeons in their daily work and are generally based on single modalities. The model- and knowledge-based in...
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