AIMC Topic: Clinical Decision-Making

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Thyroid Incidentalomas: Practice Considerations for Radiologists in the Age of Incidental Findings.

Radiologic clinics of North America
Radiologists very frequently encounter incidental findings related to the thyroid gland. Given increases in imaging use over the past several decades, thyroid incidentalomas are increasingly encountered in clinical practice, and it is important for r...

Leveraging interpretable machine learning algorithms to predict postoperative patient outcomes on mobile devices.

Surgery
Setting patient and family expectations for postoperative outcomes is an important aspect of care, a cornerstone of which is accurate, personalized, and explainable risk estimation. Modern machine learning offers a plethora of models that can effecti...

Predicting Progression to Advanced Age-Related Macular Degeneration from Clinical, Genetic, and Lifestyle Factors Using Machine Learning.

Ophthalmology
PURPOSE: Current prediction models for advanced age-related macular degeneration (AMD) are based on a restrictive set of risk factors. The objective of this study was to develop a comprehensive prediction model applying a machine learning algorithm a...

Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging.

Contrast media & molecular imaging
Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications includin...

Artificial intelligence for decision support in acute stroke - current roles and potential.

Nature reviews. Neurology
The identification and treatment of patients with stroke is becoming increasingly complex as more treatment options become available and new relationships between disease features and treatment response are continually discovered. Consequently, clini...

Evaluation of the COVID-19 Pandemic Intervention Strategies with Hesitant F-AHP.

Journal of healthcare engineering
In this study, a hesitant fuzzy AHP method is presented to help decision makers (DMs), especially policymakers, governors, and physicians, evaluate the importance of intervention strategy alternatives applied by various countries for the COVID-19 pan...

Evidence-based medicine and machine learning: a partnership with a common purpose.

BMJ evidence-based medicine
From its origins in epidemiology, evidence-based medicine has promulgated a rigorous approach to assessing the validity, impact and applicability of hypothesis-driven empirical research used to evaluate the utility of diagnostic tests, prognostic too...