AIMC Topic: Aged

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Machine Learning Models to Predict Withdrawal of Life-Sustaining Therapy in Patients With Severe Traumatic Brain Injury.

Neurology
BACKGROUND AND OBJECTIVES: Over half of all deaths after traumatic brain injury (TBI) follow the decision to withdraw life-sustaining therapy (WLST). Despite recent improvements in TBI mortality, rates of WLST have remained unchanged, potentially ref...

Machine learning-based integration of pericoronary adipose tissue and clinical risk factors for cardiovascular risk prediction in type 2 diabetes: a retrospective cohort study.

European journal of medical research
BACKGROUND: Cardiovascular disease remains the predominant cause of morbidity and mortality in individuals with type 2 diabetes mellitus (T2DM). Traditional risk models are limited in predictive accuracy. Pericoronary adipose tissue (PCAT), a novel i...

Investigating the role of depression in obstructive sleep apnea and predicting risk factors for OSA in depressed patients: machine learning-assisted evidence from NHANES.

BMC psychiatry
OBJECTIVE: The relationship between depression and obstructive sleep apnea (OSA) remains controversial. Therefore, this study aims to explore their association and utilize machine learning models to predict OSA among individuals with depression withi...

Identification and tissue-level validation of ferroptosis-related genes in small intestinal neuroendocrine neoplasms based on machine learning.

BMC gastroenterology
BACKGROUND: Small intestinal neuroendocrine neoplasms (SI-NENs), a subgroup of neuroendocrine tumors originating from neuroendocrine cells in the small intestine, present significant therapeutic challenges, and their relationship with ferroptosis-a r...

Effect of mahjong, a Chinese tiled-based game, combined with upper limb robot training on upper limb function and rehabilitation participation in Chinese stroke patients: a clinical trial protocol.

BMJ open
INTRODUCTION: Stroke is the second leading cause of death and disability creating a huge economic burden annually. Robot-assisted training (RT) is a promising therapy in stroke rehabilitation, but for the elderly, traditional 'reaching objects'" task...

High-Throughput Computing to Detect Harmful Drug-Drug Interactions in Older Adults: Protocol for a Population-Based Cohort Study.

JMIR research protocols
BACKGROUND: Drug-drug interactions (DDIs) are a major concern, especially for older adults taking multiple medications. Although Health Canada and the US Food and Drug Administration (FDA) use population-based studies to identify adverse drug events,...

Evaluation of Machine Learning Model Performance in Diabetic Foot Ulcer: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Machine learning (ML) has shown great potential in recognizing complex disease patterns and supporting clinical decision-making. Diabetic foot ulcers (DFUs) represent a significant multifactorial medical problem with high incidence and se...

Optimizing Loop Diuretic Treatment for Mortality Reduction in Patients With Acute Dyspnea Using a Practical Offline Reinforcement Learning Pipeline for Health Care: Retrospective Single-Center Simulation Study.

JMIR medical informatics
BACKGROUND: Offline reinforcement learning (RL) has been increasingly applied to clinical decision-making problems. However, due to the lack of a standardized pipeline, prior work often relied on strategies that may lead to overfitted policies and in...

Iloprost therapy achieves good clinical and radiological short and mid-term outcomes in patients with idiopathic aseptic osteonecrosis of the knee joint also in ARCO level II.

Archives of orthopaedic and trauma surgery
AIMS: The aim of this retrospective study was the evaluation of the patient-reported and radiological outcome of intravenous Iloprost therapy in the treatment of spontaneous osteonecrosis of the knee (SONK).