AIMC Topic: Female

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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...

Effectiveness of a Machine Learning-Enabled Skincare Recommendation for Mild-to-Moderate Acne Vulgaris: 8-Week Evaluator-Blinded Randomized Controlled Trial.

JMIR dermatology
BACKGROUND: Acne vulgaris (AV) is one of the most common skin disorders, with a peak incidence in adolescence and early adulthood. Topical treatments are usually used for mild to moderate AV; however, a lack of adherence to topical treatment is seen ...

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Wearable devices are increasingly used for monitoring health and detecting digital biomarkers related to chronic diseases such as metabolic syndrome (MetS). Although circadian rhythm disturbances are known to contribute to MetS, few studi...

A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation.

JMIR medical informatics
BACKGROUND: Syndrome differentiation in traditional Chinese medicine (TCM) is an ancient principle that guides disease diagnosis and treatment. Among these, the cold and hot syndromes play a crucial role in identifying the nature of the disease and g...

Specific Contribution of the Cerebellar Inferior Posterior Lobe to Motor Learning in Degenerative Cerebellar Ataxia.

Cerebellum (London, England)
BACKGROUND AND OBJECTIVE: Degenerative cerebellar ataxia, a group of progressive neurodegenerative disorders, is characterised by cerebellar atrophy and impaired motor learning. Using CerebNet, a deep learning algorithm for cerebellar segmentation, t...

Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

PloS one
BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant challenges in clinical management and is associated with poor outcomes. Survivors often...

Multimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning.

Cancer letters
Immunotherapy has become a cornerstone in the treatment of advanced gastric cancer (GC). However, identifying reliable predictive biomarkers remains a considerable challenge. This study demonstrates the potential of integrating multimodal baseline da...

Construction of a machine learning-based screening model for IgD myeloma.

Clinica chimica acta; international journal of clinical chemistry
OBJECTIVE: Immunoglobulin D (IgD) myeloma is a rare subtype of multiple myeloma (MM), comprising approximately 1 %-2 % of all MM cases. Owing to the diminished levels of IgD in serum, IgD MM manifests as subtle M protein spikes in routine serum elect...