AIMC Topic: Middle Aged

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Machine learning algorithms to predict stroke in China based on causal inference of time series analysis.

BMC neurology
IMPORTANCE: Identifying and managing high-risk populations for stroke in a targeted manner is a key area of preventive healthcare.

Enhanced neuroplasticity and gait recovery in stroke patients: a comparative analysis of active and passive robotic training modes.

BMC neurology
BACKGROUND: Stroke is a leading cause of long-term disability, with lower limb dysfunction being a common sequela that significantly impacts patients' mobility and quality of life. Robotic-assisted training has emerged as a promising intervention for...

Identifying the key factors of mercury exposure in residents of southwestern Iran using machine learning algorithms.

Environmental geochemistry and health
It is necessary to predict hair mercury (Hg) levels and specify the related effective factors to develop preventive strategies to reduce Hg exposure in different regions. This study is the first effort to investigate the effectiveness of eight machin...

Applying machine learning with MobileNetV2 model for rapid screening of vaginal discharge samples in vaginitis diagnosis.

Scientific reports
Vaginitis is a prevalent gynecological condition that impacts women's quality of life, with most women likely to experience it at least once. Traditional diagnosis involves manually observing vaginal discharge samples under a microscope. This process...

Development and validation of a 3-D deep learning system for diabetic macular oedema classification on optical coherence tomography images.

BMJ open
OBJECTIVES: To develop and validate an automated diabetic macular oedema (DME) classification system based on the images from different three-dimensional optical coherence tomography (3-D OCT) devices.

An immunohistochemistry-based classification of colorectal cancer resembling the consensus molecular subtypes using convolutional neural networks.

Scientific reports
Colorectal cancer (CRC) represents a major global disease burden with nearly 1 million cancer-related deaths annually. TNM staging has served as the foundation for predicting patient prognosis, despite variation across staging groups. The consensus m...

Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT.

BMC medical imaging
PURPOSE: To compare the image quality and pulmonary nodule detectability and measurement accuracy between deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) of chest ultra-low-dose CT (ULDCT).

Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading.

BMC medical informatics and decision making
PURPOSE: This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accuracy in high-grade gliomas.