AIMC Topic: Female

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Application of radiomics model based on lumbar computed tomography in diagnosis of elderly osteoporosis.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
A metabolic bone disease characterized by decreased bone formation and increased bone resorption is osteoporosis. It can cause pain and fracture of patients. The elderly are prone to osteoporosis and are more vulnerable to osteoporosis. In this study...

An artificial intelligence system for chronic atrophic gastritis diagnosis and risk stratification under white light endoscopy.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND AND AIMS: The diagnosis and stratification of gastric atrophy (GA) predict patients' gastric cancer progression risk and determine endoscopy surveillance interval. We aimed to construct an artificial intelligence (AI) system for GA endosco...

Designing, validation and evaluation of the expert system of "Healthy Menopause" and assessing its effect on the management of menopause symptoms: an exploratory mixed method study protocol.

Reproductive health
BACKGROUND: Menopause is a period of women's life that has the especial physical, psychological and social challenges. So provision of an effective, practical and affordable way for meeting women's related needs is important. In addition, women shoul...

Deep learning for computer-aided abnormalities classification in digital mammogram: A data-centric perspective.

Current problems in diagnostic radiology
Breast cancer is the most common type of cancer in women, and early abnormality detection using mammography can significantly improve breast cancer survival rates. Diverse datasets are required to improve the training and validation of deep learning ...

Multiparametric MRI-Based Machine Learning Models for the Characterization of Cystic Renal Masses Compared to the Bosniak Classification, Version 2019: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVE: Accurate differentiation between benign and malignant cystic renal masses (CRMs) is challenging in clinical practice. This study aimed to develop MRI-based machine learning models for differentiating between benign and malign...

Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?

International journal of radiation oncology, biology, physics
PURPOSE: Artificial intelligence (AI)-based auto-segmentation models hold promise for enhanced efficiency and consistency in organ contouring for adaptive radiation therapy and radiation therapy planning. However, their performance on pediatric compu...

Artificial Intelligence-Enabled Stool Analysis for Lactulose Titration Assistance in Hepatic Encephalopathy Through a Smartphone Application.

The American journal of gastroenterology
INTRODUCTION: Management of hepatic encephalopathy relies on self-titration of lactulose. In this feasibility trial, we assess an artificial intelligence-enabled tool to guide lactulose use through a smartphone application.

A deep learning quantification of patient specificity as a predictor of session attendance and treatment response to internet-enabled cognitive behavioural therapy for common mental health disorders.

Journal of affective disorders
BACKGROUND: Increasing an individual's ability to focus on concrete, specific detail, thus reducing the tendency toward overly broad, decontextualised generalisations about the self and world, is a target within cognitive behavioural therapy (CBT). H...

A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope images.

Artificial intelligence in medicine
The selection of embryos is a key for the success of in vitro fertilization (IVF). However, automatic quality assessment on human IVF embryos with optical microscope images is still challenging. In this study, we developed a clinical consensus-compli...