AIMC Topic: Middle Aged

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Tool or Tyrant: Guiding and Guarding Generative Artificial Intelligence Use in Nursing Education.

Creative nursing
As artificial intelligence (AI) continues to evolve rapidly, its integration into nursing education is inevitable. This article presents a narrative exploring the implementation of generative AI in nursing education and offers a guide for its strateg...

Tailoring Household Disaster Preparedness Interventions to Reduce Health Disparities: Nursing Implications from Machine Learning Importance Features from the 2018-2020 FEMA National Household Survey.

International journal of environmental research and public health
Tailored disaster preparedness interventions may be more effective and equitable, yet little is known about specific factors associated with disaster household preparedness for older adults and/or those with African American/Black identities. This st...

Integrated multi-omics analysis and machine learning developed a prognostic model based on mitochondrial function in a large multicenter cohort for Gastric Cancer.

Journal of translational medicine
BACKGROUND: Gastric cancer (GC) is a common and aggressive type of cancer worldwide. Despite recent advancements in its treatment, the prognosis for patients with GC remains poor. Understanding the mechanisms of cell death in GC, particularly those r...

Deep learning-assisted diagnosis of benign and malignant parotid tumors based on ultrasound: a retrospective study.

BMC cancer
BACKGROUND: To develop a deep learning(DL) model utilizing ultrasound images, and evaluate its efficacy in distinguishing between benign and malignant parotid tumors (PTs), as well as its practicality in assisting clinicians with accurate diagnosis.

Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study.

BMC pulmonary medicine
BACKGROUND: Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligen...

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...

An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.

Computers in biology and medicine
OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Yet premature discontinuation undermines treatment effectiveness, increasing the risk of mortality and overdose. We developed and evaluated a machine l...

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...