AIMC Topic: Clinical Decision-Making

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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...

Comparative Evaluation of the Treatment of COVID-19 with Multicriteria Decision-Making Techniques.

Journal of healthcare engineering
OBJECTIVES: The outbreak of coronavirus disease 2019 (COVID-19) was first reported in December 2019. Until now, many drugs and methods have been used in the treatment of the disease. However, no effective treatment option has been found and only case...

Reinforcement learning in surgery.

Surgery
Patients and physicians make essential decisions regarding diagnostic and therapeutic interventions. These actions should be performed or deferred under time constraints and uncertainty regarding patients' diagnoses and predicted response to treatmen...