A menstrual cycle tracking app designed for natural birth control methods (aka natural family planning).

A period tracker app with a chatbot

【⭐️ Star this repo to support women's health innovation! 】🌸 AI-powered women's health companion built with Next.js 15, React 19, Python LangGraph & Supabase. Features 8 specialized AI agents, real-time health insights, cycle prediction, fertility tracking & comprehensive wellness monitoring with 90% faster performance through Redis caching.

A TSX-based wellness and cycle care tracking app with mood journal, symptom tracker, and AI assistant.

HealthiHer is a women-centric health website providing awareness about women's healthcare. 👩‍⚕️Know about activities for well-being, try meditation😊 using our app, and much more!👩

ML enabled application for monitoring and analyzing Women`s well being.

A beginner-friendly Java project to predict next period dates and fertile windows based on cycle length.

Large Language Model based Menstrual Health Education solution

In this project we tested various learning models for a reliable women menstraul cycle accurate prediction overtime, we have used ARISTAMA, Random forest, Long-term short memeory and many more, we used synthetic data for quick analyse

My seed fund-backed little adventure

Transforms a public menstrual-cycle dataset into realistic, privacy-preserving daily logs and monthly JSON files used to seed the Kira web app.

HealthiHer is a women-centric health website providing awareness about women's healthcare. 👩‍⚕️Know about activities for well-being, try meditation😊 using our app, and much more!👩

sakhi: True independence of women

🔤 Revolutionary Braille Infinity embeddings for women's health data analysis - making complex health data accessible through tactile-friendly semantic patterns

Kira, an interactive menstrual‑health web app featuring a calendar, day details modal, and trend insights derived from curated monthly demo data.

Pregnancy Problems Got Resolved

Heart Attack Risk Predictor uses data collected from Apple Health and user's input to predict risk of a heart attack in women. Project idea by Selina Vicino and Tatiana Patton for ASU BMI. Faculty mentor: Dr. Dongwen Wang. Beta version can be installed by following the link below.

Website to help women face their sexual and other health problems. This website will help them by providing benefits of free consultations from top Women Doctors & Organisations/NGOs. Future Vision : Implementing Stream Chat, WhatsApp APIs., and setting up a larger database to handle more users.