AIMC Topic: Aged

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Association of albumin-bilirubin grade with prognosis in ICU patients with pulmonary edema: a retrospective cohort study and a predictive model based on machine learning.

BMC pulmonary medicine
BACKGROUND: The Albumin-Bilirubin (ALBI) grade was initially used to assess liver reserve function in patients with cirrhosis and has since been applied in the prognostic evaluation of various diseases. This study explored the relationship between th...

Garden classification of femoral neck fracture using deep-learning algorithm.

Scientific reports
The Garden classification, based on X-ray interpretation and established over 50 years ago, remains the standard clinical classification system for femoral neck fractures (FNFs). Yet, this classification has a high interobserver variability of 70%. W...

Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.

Scientific reports
Glioblastoma is characterized by diffuse infiltration, making accurate detection of residual disease essential for improving prognostication and guiding treatment. This study evaluates whether the volume of predicted infiltration, generated by a mach...

Development and validation of a machine learning model to predict moderate-to-severe cancer-related fatigue in breast cancer.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to establish and validate a machine learning model for predicting moderate-to-severe cancer-related fatigue (CRF) 2 years after completion of anti-tumor therapy in breast cancer patients.

Predicting and explaining life satisfaction among older adults using tree-based ensemble models and SHAP: Evidence from the digital divide survey.

PloS one
As digital transformation continues to penetrate various sectors of society, the issue of the digital divide has become increasingly prominent. Against the backdrop of accelerating population aging, the barriers that older adults face in accessing an...

Machine learning-based mortality risk prediction model for elderly diabetic patients with non-ST-segment elevation myocardial infarction using MIMIC-IV database.

Scientific reports
Non-ST-elevation myocardial infarction (NSTEMI) in elderly diabetic patients presents unique challenges in risk assessment and prognosis prediction. This study aimed to develop and validate a machine learning-based mortality risk prediction model for...

NeuroFusionNet: a hybrid EEG feature fusion framework for accurate and explainable Alzheimer's Disease detection.

Scientific reports
Alzheimer's Disease (AD) is a very common neurodegenerative disorders and early detection using electroencephalography (EEG) can enable timely intervention, however, existing computational models often lack robustness, interpretability, and clinical ...

Early prediction of vasopressor initiation in ICU sepsis patients using an interpretable EHR-based ML model.

BMC medical informatics and decision making
BACKGROUND: Early identification of septic patients who will require vasopressor support could provide a critical window for hemodynamic optimisation, yet current bedside cues often appear only when shock is imminent.

Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) and unstable angina (UA) often coexist in clinical practice, constituting a high-risk cardiovascular phenotype with a markedly increased incidence of major adverse cardiovascular even...

Neural network for natural language processing to determine treatment urgency in an ophthalmology emergency department.

The British journal of ophthalmology
BACKGROUND: In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial intelligence to develop a neural network and evaluate it...