AIMC Topic: Female

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Multi-scale machine learning model predicts muscle and functional disease progression.

Scientific reports
Facioscapulohumeral muscular dystrophy (FSHD) is a genetic neuromuscular disorder characterized by progressive muscle degeneration with substantial variability in severity and progression patterns. FSHD is a highly heterogeneous disease; however, cur...

Automatic segmentation of liver structures in multi-phase MRI using variants of nnU-Net and Swin UNETR.

Scientific reports
Accurate segmentation of the liver parenchyma, portal veins, hepatic veins, and lesions from MRI is important for hepatic disease monitoring and treatment. Multi-phase contrast enhanced imaging is superior in distinguishing hepatic structures compare...

Advancing psychological assessment: quantifying self-compassion through free-text responses and language model BERT.

Scientific reports
Self-compassion, which refers to compassion directed toward oneself, is associated with mental health and well-being. Traditionally, self-compassion has been measured and quantified using rating scales such as the Self-Compassion Scale (SCS) and Comp...

Characterising corneal changes in aniridia-related keratopathy using in vivo confocal microscopy and a self-supervised AI model.

BMJ open ophthalmology
PURPOSE: To investigate whether corneal changes observed via in vivo confocal microscopy (IVCM) in patients with aniridia-related keratopathy (ARK) reflect clinical severity.

Forecasting birth trends in Ethiopia using time-series and machine-learning models: a secondary data analysis of EDHS surveys (2000-2019).

BMJ open
OBJECTIVE: Ethiopia, the second most populous country in Africa, faces significant demographic transitions, with fertility rates playing a central role in shaping economic and healthcare policies. Family planning programmes face challenges due to fun...

Machine learning model for postpancreaticoduodenectomy haemorrhage prediction: an international multicentre cohort study.

BMJ open
OBJECTIVES: To develop and validate a machine learning model for precise risk stratification of postpancreaticoduodenectomy haemorrhage (PPH), enabling early identification of high-risk patients to guide clinical intervention.

Association Between Comorbidity Clusters and Mortality in Patients With Cancer: Predictive Modeling Using Machine Learning Approaches of Data From the United States and Hong Kong.

JMIR cancer
BACKGROUND: Patients with cancer and cancer survivors often experience multiple chronic health conditions, which can impact symptom burden and treatment outcomes. Despite the high prevalence of multimorbidity, research on cancer prognosis has predomi...

Menstrual Health Education Using a Specialized Large Language Model in India: Development and Evaluation Study of MenstLLaMA.

Journal of medical Internet research
BACKGROUND: The quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender inequality). While community-dr...

Usability and Usefulness of SMS-Based Artificial Intelligence Intervention (Mwana) on Breastfeeding Outcomes in Lagos, Nigeria: Pilot App Development Study.

JMIR formative research
BACKGROUND: Nigeria has one of the highest child mortality rates globally, with 111 deaths per 1000 live births. Exclusive breastfeeding (EBF) improves infant survival by providing essential nutrients and antibodies that protect against infections an...