AIMC Topic: Female

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A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach.

Scientific reports
Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored with visual field (VF) testing. Deep learning models (DLM) may help identify VF worsening consistently and reproducibly. In this study, we developed and ...

Acute Stress-Induced Changes in the Lipid Composition of Cow's Milk in Healthy and Pathological Animals.

Molecules (Basel, Switzerland)
Producers of milk and dairy products have been faced with the challenge of responding to European society's demand for guaranteed animal welfare production. In recent years, measures have been taken to improve animal welfare conditions on farms and e...

Application of Deep Learning Model in the Sonographic Diagnosis of Uterine Adenomyosis.

International journal of environmental research and public health
BACKGROUND: This study aims to evaluate the diagnostic performance of Deep Learning (DL) machine for the detection of adenomyosis on uterine ultrasonographic images and compare it to intermediate ultrasound skilled trainees.

Artificial intelligence breast ultrasound and handheld ultrasound in the BI-RADS categorization of breast lesions: A pilot head to head comparison study in screening program.

Frontiers in public health
BACKGROUND: Artificial intelligence breast ultrasound diagnostic system (AIBUS) has been introduced as an alternative approach for handheld ultrasound (HHUS), while their results in BI-RADS categorization has not been compared.

Applying Unsupervised Machine Learning Models to Identify Serve Performance Related Indicators in Women's Volleyball.

Research quarterly for exercise and sport
In volleyball, the effect of different factors on serve performance has usually been analyzed with traditional statistical techniques such as logistic regression or discriminant analysis. In this study, two of the main models used in unsupervised ma...

Robotic omentectomy in gynecologic oncology: surgical anatomy, indications, and a technical approach.

Journal of robotic surgery
An omentectomy is a standard component care of gynecological cancers, particularly for surgical staging and treatment for malignant ovarian neoplasms, borderline tumors, fallopian tube cancers, primary peritoneal cancers as well as certain histologic...

Prediction of knee adduction moment using innovative instrumented insole and deep learning neural networks in healthy female individuals.

The Knee
BACKGROUND: The knee adduction moment, a biomechanical risk factor of knee osteoarthritis, is typically measured in a gait laboratory with expensive equipment and inverse dynamics modeling software. We aimed to develop a framework for a portable knee...

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Radiology
Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coronary syndrome (ACS), pulmonary embolism (PE), or aortic dissection (AD), often yielding negative resu...

Age-specific risk factors for the prediction of obesity using a machine learning approach.

Frontiers in public health
Machine Learning is a powerful tool to discover hidden information and relationships in various data-driven research fields. Obesity is an extremely complex topic, involving biological, physiological, psychological, and environmental factors. One suc...

Prediction of body weight from chest radiographs using deep learning with a convolutional neural network.

Radiological physics and technology
Accurate body weights are not necessarily available in routine clinical practice. This study aimed to investigate whether body weight can be predicted from chest radiographs using deep learning. Deep-learning models with a convolutional neural networ...