AIMC Topic: Female

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Machine Learning-Based Clustering Using a 12-Lead Electrocardiogram in Patients With a Implantable Cardioverter Defibrillator to Identify Future Ventricular Arrhythmia.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: Implantable cardioverter defibrillators (ICDs) reduce mortality associated with ventricular arrhythmia in high-risk patients with cardiovascular disease. Machine learning (ML) approaches are promising tools in arrhythmia research; however...

Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Many models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive p...

Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses.

Journal of psychiatric research
Trauma is very common and associated with significant co-morbidity world-wide, particularly PTSD and frequently other mental health disorders. However, it can be challenging to identify victims of abuse as self-reports can be difficult to elicit due ...

Development of learning-based predictive models for radiation-induced atrial fibrillation in non-small cell lung cancer patients by integrating patient-specific clinical, dosimetry, and diagnostic information.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Radiotherapy (RT) in non-small cell lung cancer (NSCLC) can induce cardiac adverse events, including atrial fibrillation (AF), despite advanced RT. This study integrates patient-specific information to develop learning-based m...

Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

Thoracic cancer
BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar resection for the surgical treatment of small lung cancers, preoperative identification of this subtype...

Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...

Machine-Learning Application for Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease Using Laboratory and Body Composition Indicators.

Archives of Iranian medicine
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a significant global health burden without established curative therapies. Early detection and preventive strategies are crucial for effective MASLD management. T...