AI Medical Compendium Topic

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

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Developing a high-performance AI model for spontaneous intracerebral hemorrhage mortality prediction using machine learning in ICU settings.

BMC medical informatics and decision making
BACKGROUND: Spontaneous intracerebral hemorrhage (SICH) is a devastating condition that significantly contributes to high mortality rates. This study aims to construct a mortality prediction model for patients with SICH using four various artificial ...

A deep learning approach to remotely assessing essential tremor with handwritten images.

Scientific reports
Essential tremor (ET) is the most prevalent movement disorder, with its incidence increasing with age, significantly impacting motor functions and quality of life. Traditional methods for assessing ET severity are often time-consuming, subjective, an...

[How older people are learning through artificial intelligence-assisted health technologies : Cute seals and nervous fall sensors].

Zeitschrift fur Gerontologie und Geriatrie
BACKGROUND: With the growing use of artificial intelligence (AI) in various areas of life, AI technologies are increasingly being developed for the nursing and care of older people and are intended to contribute to greater safety for older people in ...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Scientific reports
Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is necessary especially in elderly patients. Artificial intelligence shows benefits in early warning. The aim of the study was to construct an early machin...

Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning.

Scientific reports
Tai Chi, an Asian martial art, is renowned for its health benefits, particularly in promoting healthy aging among older adults, improving balance, and reducing fall risk. However, methodological challenges hinder the objective measurement of adherenc...

A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.

Neurology
BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do not show cognitive decline over 80 weeks of follow-up. Identifying and excluding these individuals can increase power to detect treatment effects. We...

Ensemble network using oblique coronal MRI for Alzheimer's disease diagnosis.

NeuroImage
Alzheimer's disease (AD) is a primary degenerative brain disorder commonly found in the elderly, Mild cognitive impairment (MCI) can be considered a transitional stage from normal aging to Alzheimer's disease. Therefore, distinguishing between normal...

External validation of artificial intelligence for detection of heart failure with preserved ejection fraction.

Nature communications
Artificial intelligence (AI) models to identify heart failure (HF) with preserved ejection fraction (HFpEF) based on deep-learning of echocardiograms could help address under-recognition in clinical practice, but they require extensive validation, pa...

Intelligent detection and grading diagnosis of fresh rib fractures based on deep learning.

BMC medical imaging
BACKGROUND: Accurate detection and grading of fresh rib fractures are crucial for patient management but remain challenging due to the complexity of rib structures on CT images.