AIMC Topic: Middle Aged

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Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning.

BMC cancer
BACKGROUND: Distinguishing between benign and malignant testicular lesions on clinical magnetic resonance imaging (MRI) is crucial for guiding treatment planning. However, conventional MRI-based radiomics to identify testicular cancer requires expert...

Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries.

Scientific reports
The most prevalent malignancy among women is breast cancer; hence, treatment approaches are needed in consideration of tumor characteristics and disease stage but also patient preference. Two surgical options, Mastectomy and Breast Conserving Surgery...

Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.

Scientific reports
This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney injury (AKI) in diabetic patients with heart failure (HF) during hospitalization. Using data from 1,457 patients in the MIMIC-IV database, the study ide...

A deep learning approach to remotely assessing essential tremor with handwritten images.

Scientific reports
Essential tremor (ET) is the most prevalent movement disorder, with its incidence increasing with age, significantly impacting motor functions and quality of life. Traditional methods for assessing ET severity are often time-consuming, subjective, an...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Scientific reports
Limited research exists on the association between depression and heavy metal exposure. This study aims to develop an interpretable and efficient machine learning (ML) model with robust performance to identify depression linked to heavy metal exposur...

Clinicians' Perceptions and Potential Applications of Robotics for Task Automation in Critical Care: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Interest in integrating robotics within intensive care units (ICUs) has been propelled by technological advancements, workforce challenges, and heightened clinical demands, including during the COVID-19 pandemic. The integration of roboti...

Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach.

JMIR medical informatics
BACKGROUND: Chronic pain is a complex condition that affects more than a quarter of people worldwide. The development and progression of chronic pain are unique to each individual due to the contribution of interacting biological, psychological, and ...

A prediction model based on machine learning: prognosis of HBV-induced HCC male patients with smoking and drinking habits after local ablation treatment.

Frontiers in immunology
BACKGROUND: Liver cancer, particularly hepatocellular carcinoma (HCC), is a major health concern globally and in China, possibly shows recurrence after ablation treatment in high-risk patients. This study investigates the prognosis of early-stage mal...

Deciphering Insomnia: Benchmarking Automated Sleep Staging Algorithms for Complex Sleep Disorders.

Journal of sleep research
Polysomnography (PSG) is essential for diagnosing sleep disorders, but its manual interpretation is labor-intensive. Automated sleep staging algorithms are promising, yet their utility in complex sleep disorders such as insomnia remains uncertain. Th...