AIMC Topic: Adult

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Machine learning-enhanced back muscle strength prediction considering lifting condition and individual characteristics.

International journal of occupational safety and ergonomics : JOSE
This study investigated factors influencing back muscle strength, focusing on sex, forearm posture and lifting height. Lower back pain, prevalent in industries involving manual materials handling, is closely linked to back muscle strength. The study ...

Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.

Computers in biology and medicine
BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal ...

Diagnosis of Acute Appendicitis with Machine Learning-Based Computer Tomography: Diagnostic Reliability and Role in Clinical Management.

Journal of laparoendoscopic & advanced surgical techniques. Part A
Acute appendicitis (AA) is a common surgical emergency affecting 7-8% of the population. Timely diagnosis and treatment are crucial for preventing serious morbidity and mortality. Diagnosis typically involves physical examination, laboratory tests, ...

Automated identification of incidental hepatic steatosis on Emergency Department imaging using large language models.

Hepatology communications
BACKGROUND: Hepatic steatosis is a precursor to more severe liver disease, increasing morbidity and mortality risks. In the Emergency Department, routine abdominal imaging often reveals incidental hepatic steatosis that goes undiagnosed due to the ac...

Sliding-Window CNN + Channel-Time Attention Transformer Network Trained with Inertial Measurement Units and Surface Electromyography Data for the Prediction of Muscle Activation and Motion Dynamics Leveraging IMU-Only Wearables for Home-Based Shoulder Rehabilitation.

Sensors (Basel, Switzerland)
Inertial Measurement Units (IMUs) are widely utilized in shoulder rehabilitation due to their portability and cost-effectiveness, but their reliance on spatial motion data restricts their use in comprehensive musculoskeletal analyses. To overcome thi...

Development and validation of machine learning models based on stacked generalization to predict psychosocial maladjustment in patients with acute myocardial infarction.

BMC psychiatry
BACKGROUND: Psychosocial maladjustment threatens the recovery of patients with acute myocardial infarction (AMI), and early identification of patients with psychosocial maladjustment may facilitate provision of reference to targeted interventions. Th...

Integrative diagnosis of psychiatric conditions using ChatGPT and fMRI data.

BMC psychiatry
BACKGROUND: Traditional diagnostic methods for psychiatric disorders often rely on subjective assessments, leading to inconsistent diagnoses. Integrating advanced natural language processing (NLP) techniques with neuroimaging data may improve diagnos...

Characterizing Brain-Cardiovascular Aging Using Multiorgan Imaging and Machine Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the ...