FeNN-DMA: A RISC-V SoC for SNN acceleration

arXiv:2511.00732v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are a promising, energy-efficient alternative to standard Artificial Neural Networks (ANNs) and are particularly well-suited to

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Prevalence of Abnormal Uterine Bleeding and its sub-types among Adolescent Girls in India: A Systematic Review and Meta-Analysis

Objective: This study aimed to determine the national pooled prevalence of AUB, its sub-types, and dysmenorrhea among adolescent girls in India Methods: We conducted a systematic review and meta-analysis following PRISMA guidelines, searching PubMed, Embase, and Web of Science from inception to December 4, 2024. Thirty one observational studies involving adolescent girls aged 10-19 years with sample size ranging from 127 to 2000, conducted across India, were included. Due to high heterogeneity, pooled prevalence estimates were calculated using random-effects models. Results: The pooled prevalence of AUB was 19% (95% CI: 15.0-22.0%). Pooled prevalence for the most common AUB sub-types noted are – oligomenorrhea (25%), metrorrhagia (24%), and menorrhagia (18%). Additionally, the pooled prevalence of dysmenorrhea was notably high, 53% (95% CI: 43-62%). Significant heterogeneity (I2 > 90%) and regional disparities in prevalence were also observed in this review. Conclusion: High prevalence of AUB (19 %) and its sub-types highlights the urgent need for the development of a standardised screening tool to be used among adolescent girls in schools and the community, and also the integration of screening programs in adolescent reproductive and sexual health clinics to combat long-term health burden.

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