AIMC Topic: Aged

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A new intelligent system based deep learning to detect DME and AMD in OCT images.

International ophthalmology
Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular retinal diseases, playing a crucial role in diagnosing retinopathy while maintaining a non-invasive modality. The increasing volume of OCT images und...

Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning model using CT multi-level body composition parameters to detect metabolic syndrome (MS), osteoporosi...

Plasma Steroid Profiling Combined With Machine Learning for the Differential Diagnosis in Mild Autonomous Cortisol Secretion From Nonfunctioning Adenoma in Patients With Adrenal Incidentalomas.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: To assess the diagnostic value of combining plasma steroid profiling with machine learning (ML) in differentiating between mild autonomous cortisol secretion (MACS) and nonfunctioning adenoma (NFA) in patients with adrenal incidentalomas.

Advancing musculoskeletal tumor diagnosis: Automated segmentation and predictive classification using deep learning and radiomics.

Computers in biology and medicine
OBJECTIVES: Musculoskeletal (MSK) tumors, given their high mortality rate and heterogeneity, necessitate precise examination and diagnosis to guide clinical treatment effectively. Magnetic resonance imaging (MRI) is pivotal in detecting MSK tumors, a...

A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).

An ensemble model for predicting dispositions of emergency department patients.

BMC medical informatics and decision making
OBJECTIVE: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning's potential to predict ED disposit...

Opportunities and challenges of integrating artificial intelligence in China's elderly care services.

Scientific reports
The challenge of elderly care presents a formidable task, demanding the collective attention of governmental bodies and diverse sectors of society. The integration of Artificial Intelligence (AI) into the research and development of Social Elderly Ca...

External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease.

Scientific reports
A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for au...

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

BMJ health & care informatics
BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has...