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Machine learning-based pipeline for automated intracerebral hemorrhage and drain detection, quantification, and classification in non-enhanced CT images (NeuroDrAIn).

PloS one
BACKGROUND AND PURPOSE: External drainage represents a well-established treatment option for acute intracerebral hemorrhage. The current standard of practice includes post-operative computer tomography imaging, which is subjectively evaluated. The im...

Correlation between individual thigh muscle volume and grip strength in relation to sarcopenia with automated muscle segmentation.

PloS one
INTRODUCTION: Grip strength serves as a significant marker for diagnosing and assessing sarcopenia, particularly in elderly populations. The study aims to explore the relationship between individual thigh muscle volumes and grip strength, leveraging ...

Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.

Aging cell
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...

Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters.

Neurologia medico-chirurgica
This study aimed to investigate the patterns of anticoagulation therapy and coagulation parameters and to develop a prediction model to predict the type of anticoagulation therapy in geriatric patients with traumatic brain injury. A retrospective ana...

Development of a short form of the Geriatric Depression Scale-30 based on item response theory and the RiskSLIM algorithm.

General hospital psychiatry
Recently, methods of quickly and accurately screening for geriatric depression have attracted substantial attention. Short forms of the 30-item Geriatric Depression Scale have been developed based on classical test theory, such as the GDS-4, GDS-5, a...

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study.

JMIR formative research
BACKGROUND: Home hospitalization is a care modality growing in popularity worldwide. Telemedicine-driven hospital-at-home (HAH) services could replace traditional hospital departments for selected patients. Chest x-rays typically serve as a key diagn...

3-Dimensional morphological characterization of neuroretinal microglia in Alzheimer's disease via machine learning.

Acta neuropathologica communications
Alzheimer's Disease (AD) is a debilitating neurodegenerative disease that affects 47.5 million people worldwide. AD is characterised by the formation of plaques containing extracellular amyloid-β (Aβ) and neurofibrillary tangles composed of hyper-pho...

Effect of wearable robot Bot Fit's hip joint-centered assist torque and voice coach on walking.

BMC musculoskeletal disorders
BACKGROUND: The main key to the 4th industrial era is robots, and wearable robots are incorporated into human healthcare. Samsung Electronics' Bot Fit is a hip joint-centered assistive robot that can induce walking posture and energetic walking exerc...

Deep learning model for automated detection of fresh and old vertebral fractures on thoracolumbar CT.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: To develop a deep learning system for automatic segmentation of compression fracture vertebral bodies on thoracolumbar CT and differentiate between fresh and old fractures.