AIMC Topic: Aged

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[Application Practice of AI Empowering Post-discharge Specialized Disease Management in Postoperative Rehabilitation of the Lung Cancer Patients Undergoing Surgery].

Zhongguo fei ai za zhi = Chinese journal of lung cancer
BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surg...

Data-Driven Strategies for Carbimazole Titration: Exploring Machine Learning Solutions in Hyperthyroidism Control.

The Journal of clinical endocrinology and metabolism
BACKGROUND: University Hospitals Dorset (UHD) has more than 1000 thyroid patient contacts annually. These are primarily patients with autoimmune hyperthyroidism treated with carbimazole titration. Dose adjustments are made by a healthcare professiona...

Assessing the effects of immune checkpoint inhibitors on bone utilizing machine learning-assisted opportunistic quantitative computed tomography.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, yet their impact on bone health remains unclear. This study aimed to perform a retrospective cohort study utilizing routine CT scans from patients with melanoma to perform oppor...

Risk evaluation and incidence prediction of endolymphatic hydrops using multilayer perceptron in patients with audiovestibular symptoms.

Medicine
Endolymphatic hydrops (EH) has been visualized on magnetic resonance imaging (MRI) in patients with various inner ear diseases. The purpose of this study was to evaluate the prevalence and risk factors of significant EH on inner ear MRI in patients w...

Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study.

European heart journal
BACKGROUND AND AIMS: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF r...

Key Predictors of Generativity in Adulthood: A Machine Learning Analysis.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: This study aimed to explore a broad range of predictors of generativity in older adults. The study included over 60 predictors across multiple domains, including personality, daily functioning, socioeconomic factors, health status, and me...

Predicting early recurrence of hepatocellular carcinoma after thermal ablation based on longitudinal MRI with a deep learning approach.

The oncologist
BACKGROUND: Accurate prediction of early recurrence (ER) is essential to improve the prognosis of patients with hepatocellular carcinoma (HCC) underwent thermal ablation (TA). Therefore, a deep learning model system using longitudinal magnetic resona...

Machine learning-based risk assessment for cardiovascular diseases in patients with chronic lung diseases.

Medicine
The association between chronic lung diseases (CLDs) and the risk of cardiovascular diseases (CVDs) has been extensively recognized. Nevertheless, conventional approaches for CVD risk evaluation cannot fully capture the risk factors (RFs) related to ...

Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndrome.

European heart journal
BACKGROUND AND AIMS: The importance of risk stratification in patients with chest pain extends beyond diagnosis and immediate treatment. This study sought to evaluate the prognostic value of electrocardiogram feature-based machine learning models to ...