AIMC Topic: Aged

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AI-driven clinical decision support for early diagnosis and treatment planning in patients with suspected sleep apnea using clinical and demographic data before sleep studies.

NPJ primary care respiratory medicine
OBJECTIVE: This study explored the application of Machine Learning (ML) techniques to cluster patients with suspected sleep apnea (SA), based on clinical-demographic data, with the aim of optimizing diagnostic pathways and enabling more personalized ...

Face2Bone explainable AI model predicts osteoporosis risk from facial images in proof of concept study.

Scientific reports
OBJECTIVES: BMI and age are associated with the risk of osteoporosis (OP). The dynamic facial aging process involves changes in skin, muscle, fat, and facial bone structures, with facial skeletal aging affecting facial contours through volumetric red...

Predicting the timing of LC after PTGBD in elderly patients with acute cholecystitis: a machine learning approach with a web-based calculator.

Langenbeck's archives of surgery
BACKGROUND: Transcutaneous transhepatic gallbladder drainage (PTGBD) has shown significant efficacy in the treatment of elderly patients with acute cholecystitis. The goal of this study is to develop a machine learning-based web calculator aimed at p...

A machine learning-enhanced gastric cancer diagnostic method based on shell-isolated nanoparticle-enhanced Raman spectroscopy.

Nanoscale
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...

Cross-modal fusion of brain imaging and clinical data for Parkinson's disease progression prediction.

PloS one
BACKGROUND: Machine learning shows great potential in science but struggles with complex, high-dimensional multi-omics data. PD progression is long, diagnosed mainly by clinical signs. This paper proposes a novel decision fusion method to improve the...

Albumin-corrected anion gap as a predictor of 28-day mortality in acute respiratory distress syndrome: A machine learning-based retrospective study.

PloS one
BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) remains a critical condition associated with high mortality rates, prolonged hospitalization, and reduced quality of life despite advances in critical care. The albumin-corrected anion gap (ACAG)...

Plasma metabolomics disentangles T2DM- and CAD-specific dysmetabolism and identifies potential biomarkers for CAD risk escalation in diabetic patients.

Cardiovascular diabetology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major driver of coronary artery disease (CAD). Prior studies often conflate T2DM- and CAD-specific metabolic alterations, limiting insights into CAD pathogenesis in T2DM. This study aimed to distinguis...

Identification of novel vertebral development factors through UK Biobank candidate gene search and body imaging analysis.

Communications biology
Numerical variations and transitional anatomy in the human vertebral column represent a significant yet understudied aspect of skeletal development with potential effects on multiple physiological systems. Utilising UK Biobank data, we integrated gen...

Biological Age Prediction of the Cerebellar Vermis in the Human Lifespan.

Cerebellum (London, England)
The cerebellar vermis undergoes diverse structural changes with aging, yet region-specific aging patterns remain underexplored. Using Brain Structure Age (BSA), a deep learning biomarker from structural magnetic resonance imaging (MRI), we aimed to: ...

Construction and validation of a risk prediction model for complications in patients with acute leukemia based on machine learning.

Scientific reports
Early-phase severe complications remain a major cause of morbidity and mortality during induction chemotherapy for acute leukaemia. Existing risk scores capture only limited prognostic variance and are rarely well-calibrated for clinical decision sup...