AIMC Topic: Algorithms

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Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto-ML.

International journal of laboratory hematology
Artificial Intelligence (AI) and machine learning (ML) have now spawned a new field within health care and health science research. These new predictive analytics tools are starting to change various facets of our clinical care domains including the ...

Deep Learning Applied to Automated Segmentation of Geographic Atrophy in Fundus Autofluorescence Images.

Translational vision science & technology
PURPOSE: This study describes the development of a deep learning algorithm based on the U-Net architecture for automated segmentation of geographic atrophy (GA) lesions in fundus autofluorescence (FAF) images.

Future artificial intelligence tools and perspectives in medicine.

Current opinion in urology
PURPOSE OF REVIEW: Artificial intelligence has become popular in medical applications, specifically as a clinical support tool for computer-aided diagnosis. These tools are typically employed on medical data (i.e., image, molecular data, clinical var...

Kidney cancer management 3.0: can artificial intelligence make us better?

Current opinion in urology
PURPOSE OF REVIEW: Artificial intelligence holds tremendous potential for disrupting clinical medicine. Here we review the current role of artificial intelligence in the kidney cancer space.

Machine Scoring of Medical Students' Written Clinical Reasoning: Initial Validity Evidence.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: Developing medical students' clinical reasoning requires a structured longitudinal curriculum with frequent targeted assessment and feedback. Performance-based assessments, which have the strongest validity evidence, are currently not feasib...

Machine Learning: The Next Paradigm Shift in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinical setting. There are a number of existing clinical tools that use ML, and many more are in development. Physicians are important stakeholders in the h...

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Proceedings of the National Academy of Sciences of the United States of America
The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational dat...

Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.

The Journal of bone and joint surgery. American volume
BACKGROUND: Despite previous reports of improvements for athletes following hip arthroscopy for femoroacetabular impingement syndrome (FAIS), many do not achieve clinically relevant outcomes. The purpose of this study was to develop machine learning ...

Prediction of Adult Height by Machine Learning Technique.

The Journal of clinical endocrinology and metabolism
CONTEXT: Prediction of AH is frequently undertaken in the clinical setting. The commonly used methods are based on the assessment of skeletal maturation. Predictive algorithms generated by machine learning, which can already automatically drive cars ...