AIMC Topic: Aged

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Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The metastatic vascular patterns of hepatocellular carcinoma (HCC) are mainly microvascular invasion (MVI) and vessels encapsulating tumor clusters (VETC). However, most existing VETC-related radiological studies still focus on the predic...

Multi-Level Ethical Considerations of Artificial Intelligence Health Monitoring for People Living with Parkinson's Disease.

AJOB empirical bioethics
Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI can enhance our health system's ability to care for people with chronic and degenerative conditions, including Parkinson's Disease (PD). This paper r...

Efficacy and Safety of Chinese Herbal Medicine in Patients with Acute Intracerebral Hemorrhage: Protocol for a Randomized Placebo-Controlled Double-Blinded Multicenter Trial.

Cerebrovascular diseases (Basel, Switzerland)
INTRODUCTION: The popular traditional Chinese medicine (TCM) compound FYTF-919 (Zhong Feng Xing Nao prescription) may improve outcome from acute intracerebral hemorrhage (ICH) through effects on brain edema, hematoma absorption, and the immune system...

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability.

Diagnostic Test Accuracy of artificial intelligence-assisted detection of acute coronary syndrome: A systematic review and meta-analysis.

Computers in biology and medicine
BACKGROUND: Artificial intelligence (AI) has potential uses in healthcare including the detection of health conditions and prediction of health outcomes. Past systematic reviews had reviewed the accuracy of artificial neural networks (ANN) on Electro...

Automatic detection and differential diagnosis of age-related macular degeneration from color fundus photographs using deep learning with hierarchical vision transformer.

Computers in biology and medicine
Age-related macular degeneration (AMD) is a leading cause of vision loss in the elderly, highlighting the need for early and accurate detection. In this study, we proposed DeepDrAMD, a hierarchical vision transformer-based deep learning model that in...

Cross-sectional area and fat infiltration of the lumbar spine muscles in patients with back disorders: a deep learning-based big data analysis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Validated deep learning models represent a valuable option to perform large-scale research studies aiming to evaluate muscle quality and quantity of paravertebral lumbar muscles at the population level. This study aimed to assess lumbar spin...

Cholesterol Levels, Hormone Replacement Therapy, and Incident Dementia among Older Adult Women.

Nutrients
Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect for preventing dementia in post-menopausal women. However, the results were still controversial. The association between cholesterol levels and incident...

Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning.

Surgery today
PURPOSE: To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.

Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.

European radiology
OBJECTIVES: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model.