AIMC Topic: Middle Aged

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A study of "left against medical advice" emergency department patients: an optimized explainable artificial intelligence framework.

Health care management science
The issue of left against medical advice (LAMA) patients is common in today's emergency departments (EDs). This issue represents a medico-legal risk and may result in potential readmission, mortality, or revenue loss. Thus, understanding the factors ...

Deep learning-aided respiratory motion compensation in PET/CT: addressing motion induced resolution loss, attenuation correction artifacts and PET-CT misalignment.

European journal of nuclear medicine and molecular imaging
PURPOSE: Respiratory motion (RM) significantly impacts image quality in thoracoabdominal PET/CT imaging. This study introduces a unified data-driven respiratory motion correction (uRMC) method, utilizing deep learning neural networks, to solve all th...

Automatic deep learning segmentation of the hippocampus on high-resolution diffusion magnetic resonance imaging and its application to the healthy lifespan.

NMR in biomedicine
Diffusion tensor imaging (DTI) can provide unique contrast and insight into microstructural changes with age or disease of the hippocampus, although it is difficult to measure the hippocampus because of its comparatively small size, location, and sha...

Predicting serious postoperative complications and evaluating racial fairness in machine learning algorithms for metabolic and bariatric surgery.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: Predicting the risk of complications is critical in metabolic and bariatric surgery (MBS).

Intraoperative detection of parathyroid glands using artificial intelligence: optimizing medical image training with data augmentation methods.

Surgical endoscopy
BACKGROUND: Postoperative hypoparathyroidism is a major complication of thyroidectomy, occurring when the parathyroid glands are inadvertently damaged during surgery. Although intraoperative images are rarely used to train artificial intelligence (AI...

A Novel Artificial Intelligence-Based Parameterization Approach of the Stromal Landscape in Merkel Cell Carcinoma: A Multi-Institutional Study.

Laboratory investigation; a journal of technical methods and pathology
Tumor-stroma ratio (TSR) has been recognized as a valuable prognostic indicator in various solid tumors. This study aimed to examine the clinicopathologic relevance of TSR in Merkel cell carcinoma (MCC) using artificial intelligence (AI)-based parame...

Characterization of cardiac resynchronization therapy response through machine learning and personalized models.

Computers in biology and medicine
INTRODUCTION: The characterization and selection of heart failure (HF) patients for cardiac resynchronization therapy (CRT) remain challenging, with around 30% non-responder rate despite following current guidelines. This study aims to propose a nove...

Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification.

Scientific reports
Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the incorporation of hair minerals into ML models remains unexplored. This study aimed to develop ML models for predicting low bone mass (LBM) using health...

Movement- and Posture-based Measures of Sedentary Patterns and Associations with Metabolic Syndrome in Hispanic/Latino and non-Hispanic Adults.

Journal of racial and ethnic health disparities
BACKGROUND: Sedentary behavior has been identified as a significant risk factor for Metabolic Syndrome (MetS). However, it is unclear if the sedentary pattern measurement approach (posture vs. movement) impacts observed associations or if association...