AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Clinical Decision-Making

Showing 281 to 290 of 597 articles

Clear Filters

Application Prospect of Artificial Intelligence in Rehabilitation and Management of Myasthenia Gravis.

BioMed research international
Myasthenia gravis (MG) is a chronic autoimmune disease of the nervous system, which is still incurable. In recent years, with the progress of immunosuppressive and supportive treatment, the therapeutic effect of MG in the acute stage is satisfactory,...

Hierarchical deep learning models using transfer learning for disease detection and classification based on small number of medical images.

Scientific reports
Deep learning is being employed in disease detection and classification based on medical images for clinical decision making. It typically requires large amounts of labelled data; however, the sample size of such medical image datasets is generally s...

Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study.

Journal of medical systems
Early identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the accepta...

Development and Validation of Machine Learning-based Model for the Prediction of Malignancy in Multiple Pulmonary Nodules: Analysis from Multicentric Cohorts.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Nodule evaluation is challenging and critical to diagnose multiple pulmonary nodules (MPNs). We aimed to develop and validate a machine learning-based model to estimate the malignant probability of MPNs to guide decision-making.

Artificial intelligence for a personalized diagnosis and treatment of atrial fibrillation.

American journal of physiology. Heart and circulatory physiology
Although atrial fibrillation (AF) is the most common cardiac arrhythmia, its early identification, diagnosis, and treatment is still challenging. Due to its heterogeneous mechanisms and risk factors, targeting an individualized treatment of AF demand...

Using Natural Language Processing and Machine Learning to Identify Hospitalized Patients with Opioid Use Disorder.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Opioid use disorder (OUD) represents a global public health crisis that challenges classic clinical decision making. As existing hospital screening methods are resource-intensive, patients with OUD are significantly under-detected. An automated and a...

Co-designing diagnosis: Towards a responsible integration of Machine Learning decision-support systems in medical diagnostics.

Journal of evaluation in clinical practice
RATIONALE: This paper aims to show how the focus on eradicating bias from Machine Learning decision-support systems in medical diagnosis diverts attention from the hermeneutic nature of medical decision-making and the productive role of bias. We want...