AIMC Topic: Aged

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Development and validation of an interpretable Random Forest model for predicting recurrence after endoscopic submucosal dissection in superficial oesophageal squamous cell carcinoma.

Annals of medicine
BACKGROUND: Currently, endoscopic submucosal dissection (ESD) has become the preferred treatment for superficial oesophageal squamous cell carcinoma (SESCC). However, due to the residual background mucosa, some patients are still at risk of postopera...

Health-related quality of life among healthcare workers: a comparative analysis using regression, conditional tree and forests.

BMC public health
BACKGROUND: Considering the potential importance of health care workers (HCWs) in maintaining and improving the health of society, we decided to investigate the factors affecting the health-related quality of life (HRQoL) of HCWs using machine learni...

Effects of bisphosphonates after denosumab discontinuation and treatment effect heterogeneity using causal machine learning.

Scientific reports
Discontinuation of denosumab is associated with a rebound increase in osteoporotic fracture (OF) risk, and bisphosphonates (BPs) are commonly recommended as sequential therapy to mitigate this risk. However, their real-world effectiveness-and whether...

Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.

BMC geriatrics
BACKGROUND: Although no definitive treatment exists, 30-40% of postoperative delirium cases are preventable through early risk identification and intervention. Therefore our aim was to develop and evaluate a postoperative delirium risk prediction mod...

A baseline study of interpretable machine learning using GC-MS breath VOCs for classifying asthma, bronchiectasis, and COPD.

Scientific reports
Accurate differentiation among asthma, bronchiectasis, and chronic obstructive pulmonary disease (COPD) remains a critical challenge due to overlapping clinical symptoms and limitations of conventional diagnostic tools. This study establishes a trans...

Evaluating Multiple Input Strategies of Large Language Models for Gallbladder Polyps on Ultrasound: Comparative Study.

JMIR medical informatics
BACKGROUND: Gallbladder polyps have a high prevalence and are predominantly benign lesions, often detected via ultrasound. They impose diagnostic burdens on radiologists while generating substantial patient demand for report interpretation. Benign po...

Adherence to Accelerometer Use in Older Adults Undergoing mHealth Cardiac Rehabilitation: Secondary Analysis of a Randomized Clinical Trial.

Journal of medical Internet research
BACKGROUND: Wearable accelerometers, which continuously record physical activity metrics, are commonly used in mobile health-enabled cardiac rehabilitation (mHealth-CR). The association between adherence to accelerometer use during mHealth-CR and imp...

Predictive modeling of hematoma expansion from non-contrast computed tomography in spontaneous intracerebral hemorrhage patients.

eLife
Hematoma expansion is a consistent predictor of poor neurological outcome and mortality after spontaneous intracerebral hemorrhage (ICH). An incomplete understanding of its biophysiology has limited early preventative intervention. Transport-based mo...

Deep learning-based MRI model for predicting P53-mutated hepatocellular carcinoma.

BMC medical imaging
BACKGROUND: The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-based deep learning m...

A Machine Learning Model Based on Clinical Factors to Predict the Efficacy of First-Line Immunochemotherapy for Patients With Advanced Gastric Cancer: Retrospective Study.

JMIR medical informatics
BACKGROUND: The development of immunotherapy has provided new hope for patients with advanced gastric cancer (AGC). However, due to the high heterogeneity of the disease, the efficacy of first-line immunochemotherapy varies among patients. There is s...