There are 0 repository under fertility topic.
Sperm detection and tracking methods from this paper: https://arxiv.org/abs/2002.04034
PeriodTracker - Your Personal Health Companion
This app projects a user-defined Leslie (age-classified) matrix to examine population changes through time.
Code for the paper "Human capital mediates natural selection in contemporary humans"
Open Fertility is an open-source project dedicated to advancing fertility analysis and prediction through machine learning.
Android app that helps women interpret ovulation and pregnancy test strips by quantifying using the phone's camera. Still works on Android 10. Original dev open-sourced because of lack of time to maintain (kudos to them). Mirror of https://gitlab.com/colnix/fta
Applied Demography Toolbox
Excel sheets, Stata do files and other resources related to the article 'Pathways to Low Fertility' by Ian Timaeus and Tom Moultrie
PrESOgenesis is a Support Vector Machine-based classifier to predict the spermatogenesis/embryogenesis/oogenesis related proteins based on 1920 meaningful protein sequence features.
Hauer, Baker, and Brown's Implied Total Fertility Rate Calculator
R code to reproduce models testing for cross-national human fertility patterns relative to underlying drivers
Farid FLICI personal webpage
A web application for predicting the chance of an IVF/ICSI cycle yielding a D5 embryo suitable for transfer or freezing.
Predicting the probability of an IVF patient having an embryo suitable for D5 transfer or freezing.
Artifacts for the JIB Bahmni distribution
👶 Has COVID-19 made us not want to have children? - analysis of birth rate determinants
The Basal Body Temperature (BBT) Tracker is designed to help individuals monitor and analyze their daily basal body temperatures throughout their menstrual cycle. By tracking these temperatures over time, users can gain insights into their fertility patterns and menstrual health.
This project analyzes the demographic transition in the United States, focusing on historical changes in fertility and mortality patterns. Using models like Lee-Carter and Renshaw-Haberman, it explores the impact of socio-economic factors, healthcare advancements, and cultural shifts on population dynamics, forecasting trends for the next 50 years.
Exploring the genetic and behavioral factors behind the fertility-longevity trade-off, this project uses survival analysis and polygenic risk scores to uncover the complex interplay of reproductive behavior, socio-demographic influences, and genetic predispositions in shaping human lifespan.
Fertility , Longevity and Economic Growth
A deep learning computer vision model to predict the fertility status of women based on their cervical mucus images.
Tanulmányomban az egy főre eső GDP és munkanélküliség teljes termékenységi arányszámra gyakorolt hatását elemzem. A választott eszközök között szerepel az Engel-Granger kointegrációs teszt, amellyel megerősítettem a hipotézist, hogy szomszédos országok termékenységi rátájának alakulása általában nagyobb egyezőséget mutat, melynek magyarázata lehet a közös gazdasági környezet és kultúra. Második választott eszköz a vektor autoregresszív modellek készítése, melyekből levonható konklúzió, hogy a GDP/fő pozitívan, míg a munkanélküliségi ráta negatívan befolyásolja a termékenységi arányszámot, de kettő közül előbbi alakulása fontosabb. Harmadik eszközként panel modellt választottam a Magyarországi megyékre, mely tanulmányom fő hozzáadott értékét képviseli. Statisztikailag szignifikáns magyarázóváltozónak bizonyult GDP/fő, hatása egy évvel később érvényesül, továbbá határhatása csökkenő, és 7 340 000 Ft-ig, amely fölött egyedül Budapest van, növeli a TTA értékét. Ez alapján elmondható, hogy a termékenységi ráta növelése szempontjából a szegényebb régiók egy főre eső bruttó kibocsátásának emelése javasolt.
The use of machine learning on the Fertility and Women's Labor Supply data set to predict whether someone will want more kids based on their age, ethinicity, work hours, and gender of their 1st child?
Fertility Diagnoser is a web application that utilizes machine learning to predict fertility levels. By inputting relevant data such as age and other factors, users can receive personalized predictions about their fertility. The application seamlessly integrates React and Python, offering a user-friendly interface and accurate predictions.
This repository contains the code required to perform the data processing and analysis associated with the manuscript submitted to Nature under the name "Maladaptive Genetic Assortment in Humans
Machine learning in python case study to predict fertility (from the UCI database) and optimize cost function/threshold using cross validation
Descriptive Analysis of Fertility Rates and Income based data
Woman fertility depends strongly on child mortality
A groundbreaking app for fertility awareness
Visualises access to Assisted Reproductive Technology clinics in Australia, as well as fertility data globally
Eddie's Brass Relational Gompertz Fertility Model Code
Laura Symul's personal website