AIMC Topic: Aged
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Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.
Nature communications
Mar 6, 2025
Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditional methods rely on Computed Tomography Pulmonary Angiography (CTPA), which requires contrast agents with potential health risks. Non-contrast CT, a s...
Controlling nutritional status score predicts posthepatectomy liver failure: an online interpretable machine learning prediction model.
European journal of gastroenterology & hepatology
Mar 5, 2025
BACKGROUND AND AIMS: Posthepatectomy liver failure (PHLF) remains a severe complication after hepatectomy for hepatocellular carcinoma (HCC) and accurate preoperative evaluation and predictive measures are urgently needed. We investigated the impact ...
Development of Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer Patients Using Clinical Risk Factors, Patient-Reported Outcomes, and Serum Cytokine Biomarkers.
Clinical breast cancer
Mar 5, 2025
BACKGROUND: Radiation dermatitis (RD) is a significant side effect of radiotherapy experienced by breast cancer patients. Severe symptoms include desquamation or ulceration of irradiated skin, which impacts quality of life and increases healthcare co...
Altered Gut Microbiome Composition and Function in Individuals with Complex Regional Pain Syndrome.
Anesthesiology
Mar 5, 2025
BACKGROUND: Complex regional pain syndrome is a chronic pain syndrome typically affecting a limb. It is characterized by severe spontaneous and evoked pain, along with vasomotor, autonomic, and motor signs and symptoms. Although dysregulation in seve...
Dual-type deep learning-based image reconstruction for advanced denoising and super-resolution processing in head and neck T2-weighted imaging.
Japanese journal of radiology
Mar 5, 2025
PURPOSE: To assess the utility of dual-type deep learning (DL)-based image reconstruction with DL-based image denoising and super-resolution processing by comparing images reconstructed with the conventional method in head and neck fat-suppressed (Fs...
Added value of artificial intelligence for the detection of pelvic and hip fractures.
Japanese journal of radiology
Mar 5, 2025
PURPOSE: To assess the added value of artificial intelligence (AI) for radiologists and emergency physicians in the radiographic detection of pelvic fractures.
Utilizing Machine Learning Techniques to Predict Negative Remodeling in Uncomplicated Type B Intramural Hematoma.
Annals of vascular surgery
Mar 5, 2025
BACKGROUND: To evaluate the effectiveness of machine learning (ML) techniques in predicting negative remodeling in uncomplicated Stanford type B intramural hematoma (IMHB) during the acute phase.
Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.
Computers in biology and medicine
Mar 5, 2025
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
Suicide, Completed
Predictive Learning Models
Psychological Well-Being
Natural Language Processing
United States Department of Veterans Affairs
Humans
Veterans
United States Department of Defense
Case-Control Studies
Young Adult
Adolescent
Adult
Suicide Prevention
Electronic Health Records
Male
United States
Female
Middle Aged
Aged
Risk Assessment
Aged, 80 and over
Joint fusion of EHR and ECG data using attention-based CNN and ViT for predicting adverse clinical endpoints in percutaneous coronary intervention patients.
Computers in biology and medicine
Mar 5, 2025
Predicting post-Percutaneous Coronary Intervention (PCI) outcomes is crucial for effective patient management and quality improvement in healthcare. However, achieving accurate predictions requires the integration of multimodal clinical data, includi...
Development of Hybrid radiomic Machine learning models for preoperative prediction of meningioma grade on multiparametric MRI.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mar 5, 2025
PURPOSE: To develop and compare machine learning models for distinguishing low and high grade meningiomas on multiparametric MRI.
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