AIMC Topic: Female

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Development and evaluation of a deep learning framework for pelvic and sacral tumor segmentation from multi-sequence MRI: a retrospective study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurate segmentation of pelvic and sacral tumors (PSTs) in multi-sequence magnetic resonance imaging (MRI) is essential for effective treatment and surgical planning.

Machine learning based model for the early detection of Gestational Diabetes Mellitus.

BMC medical informatics and decision making
BACKGROUND: Gestational Diabetes Mellitus (GDM) is one of the most common medical complications during pregnancy. In the Gulf region, the prevalence of GDM is higher than in other parts of the world. Thus, there is a need for the early detection of G...

Machine learning-derived diagnostic model of epithelial ovarian cancer based on gut microbiome signatures.

Journal of translational medicine
BACKGROUND: Prior studies have elucidated that alterations in gut microbiota are associated with a spectrum of tumors and metabolic disorders. However, the diagnostic value of gut microbiota in epithelial ovarian cancer remains insufficiently investi...

Integration of artificial intelligence in radiology education: a requirements survey and recommendations from faculty radiologists, residents, and medical students.

BMC medical education
BACKGROUND: To investigate the perspectives and expectations of faculty radiologists, residents, and medical students regarding the integration of artificial intelligence (AI) in radiology education, a survey was conducted to collect their opinions a...

Biological age prediction and NAFLD risk assessment: a machine learning model based on a multicenter population in Nanchang, Jiangxi, China.

BMC gastroenterology
BACKGROUND: The objective was to develop a biological age prediction model (NC-BA) for the Chinese population to enrich the relevant studies in this population. And to investigate the association between accelerated age and NAFLD.

Development and validation of machine learning-based prediction model for outcome of cardiac arrest in intensive care units.

Scientific reports
Cardiac arrest (CA) poses a significant global health challenge and often results in poor prognosis. We developed an interpretable and applicable machine learning (ML) model for predicting in-hospital mortality of CA patients who survived more than 7...

ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with interpretable machine learning.

Scientific reports
Early detection of malignant thyroid nodules is crucial for effective treatment, but traditional diagnostic methods face challenges such as variability in expert opinions and limited integration of advanced imaging techniques. This prospective cohort...

Three-dimensional markerless surface topography approach with convolutional neural networks for adolescent idiopathic scoliosis screening.

Scientific reports
Adolescent idiopathic scoliosis (AIS) is a three-dimensional lateral and torsional deformity of the spine, affecting up to 5% of the population. Traditional scoliosis screening methods exhibit limited accuracy, leading to unnecessary referrals and ex...

Sex bias consideration in healthcare machine-learning research: a systematic review in rheumatoid arthritis.

BMJ open
OBJECTIVE: To assess the acknowledgement and mitigation of sex bias within studies using supervised machine learning (ML) for improving clinical outcomes in rheumatoid arthritis (RA).