AI Medical Compendium Topic

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

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COVID-19 from symptoms to prediction: A statistical and machine learning approach.

Computers in biology and medicine
During the COVID-19 pandemic, the analysis of patient data has become a cornerstone for developing effective public health strategies. This study leverages a dataset comprising over 10,000 anonymized patient records from various leading medical insti...

Development of a Predictive Hospitalization Model for Skilled Nursing Facility Patients.

Journal of the American Medical Directors Association
OBJECTIVES: Identifying skilled nursing facility (SNF) patients at risk for hospitalization or death is of interest to SNFs, patients, and patients' families because of quality measures, financial penalties, and limited clinical staffing. We aimed to...

The application of machine learning for identifying frailty in older patients during hospital admission.

BMC medical informatics and decision making
BACKGROUND: Early identification of frail patients and early interventional treatment can minimize the frailty-related medical burden. This study investigated the use of machine learning (ML) to detect frailty in hospitalized older adults with acute ...

Automated ventricular segmentation and shunt failure detection using convolutional neural networks.

Scientific reports
While ventricular shunts are the main treatment for adult hydrocephalus, shunt malfunction remains a common problem that can be challenging to diagnose. Computer vision-derived algorithms present a potential solution. We designed a feasibility study ...

Explainability of CNN-based Alzheimer's disease detection from online handwriting.

Scientific reports
With over 55 million people globally affected by dementia and nearly 10 million new cases reported annually, Alzheimer's disease is a prevalent and challenging neurodegenerative disorder. Despite significant advancements in machine learning technique...

Accelerating FLAIR imaging via deep learning reconstruction: potential for evaluating white matter hyperintensities.

Japanese journal of radiology
PURPOSE: To evaluate deep learning-reconstructed (DLR)-fluid-attenuated inversion recovery (FLAIR) images generated from undersampled data, compare them with fully sampled and rapidly acquired FLAIR images, and assess their potential for white matter...

A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly.

Journal of affective disorders
BACKGROUND: With the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China ...

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages.

Informatics for health & social care
INTRODUCTION: The world's population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quali...