AIMC Topic: Aged, 80 and over

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Machine Learning Models to Predict Bone Metastasis Risk in Patients With Lung Cancer.

Cancer medicine
INTRODUCTION: The aim of this study was to find the most appropriate variables to input into machine learning algorithms to identify those patients with primary lung malignancy with high risk for metastasis to the bone.

Machine learning-based clustering identifies obesity subgroups with differential multi-omics profiles and metabolic patterns.

Obesity (Silver Spring, Md.)
OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct ca...

Deep Learning Reconstruction in Abdominopelvic Contrast-Enhanced CT for The Evaluation of Hemorrhages.

Radiologic technology
PURPOSE: To investigate the effects of deep learning reconstruction on depicting arteries and providing suitable images for the evaluation of hemorrhages with abdominopelvic contrast-enhanced computed tomography (CT) compared with hybrid iterative re...

Precise Image-level Localization of Intracranial Hemorrhage on Head CT Scans with Deep Learning Models Trained on Study-level Labels.

Radiology. Artificial intelligence
Purpose To develop a highly generalizable weakly supervised model to automatically detect and localize image-level intracranial hemorrhage (ICH) by using study-level labels. Materials and Methods In this retrospective study, the proposed model was pr...

Predicting physical functioning status in older adults: insights from wrist accelerometer sensors and derived digital biomarkers of physical activity.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Conventional physical activity (PA) metrics derived from wearable sensors may not capture the cumulative, transitions from sedentary to active, and multidimensional patterns of PA, limiting the ability to predict physical function impairme...

Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.

Journal of neuropathology and experimental neurology
Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platfo...

Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors.

World journal of gastroenterology
BACKGROUND: Although immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in some patients diagnosed with gastric cancer (GC), existing prognostic markers are not universally applicable to all patients with advanced GC.

[Early gait analysis after total knee arthroplasty based on artificial intelligence dynamic image recognition].

Zhongguo gu shang = China journal of orthopaedics and traumatology
OBJECTIVE: To explore early postoperative gait characteristics and clinical outcomes after total knee arthroplasty (TKA).

Analysis of In-Home Movement Patterns for Depression Assessment in Older Adults - A Feasibility Study.

Studies in health technology and informatics
Depression significantly impacts the wellbeing of older Australians, posing considerable challenges to their overall quality of life. This study aimed to detect in-home movement patterns of participants that could be indicative of depressive states. ...

Tailoring nonsurgical therapy for elderly patients with head and neck squamous cell carcinoma: A deep learning-based approach.

Medicine
To assess deep learning models for personalized chemotherapy selection and quantify the impact of baseline characteristics on treatment efficacy for elderly head and neck squamous cell carcinoma (HNSCC) patients who are not surgery candidates. A comp...