Privacy focused period tracking!
Period tracking app - Free, offline, and open source.
PERIOD CYCLE PREDICTION©: Predictive Modeling of Menstrual Cycle Length: A Time Series Forecasting Approach ♀ https://arxiv.org/pdf/2308.07927.pdf
Sakhi, a mobile-first app tailored for women, encompasses daily journals, safety features, community, and holistic health tools. Elevate your well-being with Sakhi, your dedicated companion for empowerment, connection, and growth.
A web app to track mentrual cycles, health, and hygiene - work in progress
MensturalMate is a simple menu driven period calculator build in C language as part of my mini-project in MCA Semester 1
Menstruated is a place where women share their first-period stories, feelings, emotions through blogs. Can track your periods and get notified early through the mail. They should know that you are not alone in the fight against PCOS by-polls which shown in the graph and many other questions. Can know the myths/facts, self-care during periods.
✅ Better cycle predictions for your app. Accurate, private, and easy to integrate.
Flowlytics is privacy-centric period tracker app built with Flutter and delivers smart cycle predictions using on-device machine learning algorithms with detailed visualization
A comprehensive menstrual health tracking platform with intelligent cycle predictions, symptom monitoring, mood logging, and personalized wellness insights. Built with React, Express, and MongoDB to help users understand and manage their reproductive health through data-driven analytics.
A monorepo for Nepali Calendar App for web, mobile.
Command line tool to plot a graph of cycles exported from Apple Health or Withings Health Mate.
Menstrual Cycle Tracker made during CBIT Hacktoberfest'24
selfhostable, dead simple, period tracker as a progressive web app
Private, self-hosted period & cycle tracker with predictions, AI insights and a Home Assistant integration.
OpenPeriods is an Open-Source Browser based Period (menstruation) Tracking System for women written in Svelte.
🌟 LunaBloom: Empower your menstrual health journey with personalized tracking, predictions, and AI assistance.
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.
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