AIMC Topic: Machine Learning

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Artificial intelligence and ophthalmic surgery.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Artificial intelligence and deep learning have become important tools in extracting data from ophthalmic surgery to evaluate, teach, and aid the surgeon in all phases of surgical management. The purpose of this review is to highlig...

Artificial intelligence in myopia: current and future trends.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Myopia is one of the leading causes of visual impairment, with a projected increase in prevalence globally. One potential approach to address myopia and its complications is early detection and treatment. However, current healthcar...

Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization.

Current opinion in ophthalmology
PURPOSE OF REVIEW: This article aims to discuss the current state of resources enabling the democratization of artificial intelligence (AI) in ophthalmology.

Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data.

Journal of animal science
Wearable sensors have been explored as an alternative for real-time monitoring of cattle feeding behavior in grazing systems. To evaluate the performance of predictive models such as machine learning (ML) techniques, data cross-validation (CV) approa...

Interpretable Machine Learning Model for Early Prediction of Mortality in ICU Patients with Rhabdomyolysis.

Medicine and science in sports and exercise
PURPOSE: Rhabdomyolysis (RM) is a complex set of clinical syndromes that involves the rapid dissolution of skeletal muscles. Mortality from RM is approximately 10%. This study aimed to develop an interpretable and generalizable model for early mortal...

Invited Commentary: Quantitative Bias Analysis Can See the Forest for the Trees.

American journal of epidemiology
The accompanying article by Jiang et al. (Am J Epidemiol. 2021;190(9):1830-1840) extends quantitative bias analysis from the realm of statistical models to the realm of machine learning algorithms. Given the rooting of statistical models in the spiri...

Demystifying machine learning: a primer for physicians.

Internal medicine journal
Machine learning is a tool for analysing digitised data sets and formulating predictions that can optimise clinical decision-making. It aims to identify complex patterns in large data sets and encode them into models that can then classify new unseen...

Radiomics and machine learning applications in rectal cancer: Current update and future perspectives.

World journal of gastroenterology
The high incidence of rectal cancer in both sexes makes it one of the most common tumors, with significant morbidity and mortality rates. To define the best treatment option and optimize patient outcome, several rectal cancer biological variables mus...