AIMC Topic: Clinical Decision-Making
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Revolutionizing clinical decision making through deep learning and topic modeling for pathway optimization.
Scientific reports
Aug 6, 2025
Optimizing clinical pathways is pivotal for enhancing healthcare delivery, yet traditional methods are increasingly insufficient in the face of complex, personalized medical demands. This paper introduces an innovative optimization framework that fus...
Initiation of antifibrotic treatment in fibrosing interstitial lung disease: is the clock ticking till proven progression?
European respiratory review : an official journal of the European Respiratory Society
Aug 6, 2025
Several interstitial lung diseases (ILDs) with different aetiologies and pathogenic mechanisms may exhibit a progressive behaviour, similar to idiopathic pulmonary fibrosis, with comparable functional decline and early mortality. Progressive pulmonar...
Evidence Based Gait Analysis Interpretation Tools (EB-GAIT) treatment recommendation and outcome prediction models to support decision-making based on clinical gait analysis data.
PloS one
Jul 29, 2025
Clinical gait analysis (CGA) has historically relied on clinician experience and judgment, leading to modest, stagnant, and unpredictable outcomes. This paper introduces Evidence-Based Gait Analysis Interpretation Tools (EB-GAIT), a novel framework l...
When time is of the essence: ethical reconsideration of XAI in time-sensitive environments.
Journal of medical ethics
Jul 23, 2025
The objective of explainable artificial intelligence systems designed for clinical decision support (XAI-CDSS) is to enhance physicians' diagnostic performance, confidence and trust through the implementation of interpretable methods, thus providing ...
Multi-task reinforcement learning and explainable AI-Driven platform for personalized planning and clinical decision support in orthodontic-orthognathic treatment.
Scientific reports
Jul 8, 2025
This study presents a novel clinical decision support platform for orthodontic-orthognathic treatment that integrates multi-task reinforcement learning with explainable artificial intelligence. The platform addresses the challenges of personalized tr...
It is not about autonomy: realigning the ethical debate on substitute judgement and AI preference predictors in healthcare.
Journal of medical ethics
Jul 7, 2025
This article challenges two dominant assumptions in the current ethical debate over the use of algorithmic Personalised Patient Preference Predictors (P4) in substitute judgement for incapacitated patients. First, I question the belief that the auton...
A narrative review of the use of PROMs and machine learning to impact value-based clinical decision-making.
BMC medical informatics and decision making
Jul 4, 2025
PURPOSE: This review summarises the studies which combined Patient Reported Outcome Measures (PROMs) and Machine Learning statistical computational techniques, to predict patient post-intervention outcomes. The aim of the project was to inform those ...
Perspectives of Health Care Professionals on the Use of AI to Support Clinical Decision-Making in the Management of Multiple Long-Term Conditions: Interview Study.
Journal of medical Internet research
Jul 4, 2025
BACKGROUND: Managing multiple long-term conditions (MLTC) is complex. Clinical management guidelines are typically focused on individual conditions and lack a robust evidence base for patients with MLTC. MLTC management is largely delivered in primar...
Artificial Intelligence in Clinical Nutrition: Bridging Data Analytics and Nutritional Care.
Current nutrition reports
Jul 3, 2025
PURPOSE OF REVIEW: This review explores how artificial intelligence can help advance clinical nutrition and address nutrition education and practice challenges. It highlights the role of AI, mainly through advanced clinical decision-making using gene...
Exploring the medical ethical limitations of GPT-4 in clinical decision-making scenarios: a pilot survey.
Frontiers in public health
May 29, 2025
BACKGROUND: This study aims to conduct an examination of GPT-4's tendencies when confronted with ethical dilemmas, as well as to ascertain their ethical limitations within clinical decision-makings.
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