From a01ea2a32c523440d2a9faf66a188c38f43ead82 Mon Sep 17 00:00:00 2001 From: Denish Awajo Date: Tue, 22 Oct 2024 21:35:12 +0300 Subject: [PATCH] Update README.md --- README.md | 24 +++++++++++++++--------- 1 file changed, 15 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 665f76a..dafc2d6 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,18 @@ -**Safe Mom: Predictive Machine Learning for Preeclampsia** -Project Overview: Safe Mom is a predictive machine learning solution aimed at helping expectant mothers and healthcare professionals identify the likelihood of developing preeclampsia during the early stages of pregnancy. By leveraging patient data collected during the eighth week, the model provides valuable insights to mitigate risks and improve maternal health outcomes. +#**Safe Mom: Predictive Machine Learning for Preeclampsia** +##**Project Overview:** -Project Goals: -Predict early: Identify the likelihood of preeclampsia at the eighth week of pregnancy. -Enhance care: Empower healthcare providers to make informed decisions. -Improve outcomes: Provide mothers with early intervention strategies for better health. -Key Features: -Machine Learning Model: Utilizes advanced predictive algorithms to assess preeclampsia risk. -Patient Data: Collects relevant health information, including: +>Safe Mom is a predictive machine learning solution aimed at helping expectant mothers and healthcare professionals identify the likelihood of developing preeclampsia during the early stages of pregnancy. By leveraging patient data collected during the eighth week, the model provides valuable insights to mitigate risks and improve maternal health outcomes. + +##**Project Goals:** + +-*Predict early:* Identify the likelihood of preeclampsia at the eighth week of pregnancy. +-*Enhance care:* Empower healthcare providers to make informed decisions. +-*Improve outcomes:* Provide mothers with early intervention strategies for better health. + +##**Key Features:** + +-*Machine Learning Model:* Utilizes advanced predictive algorithms to assess preeclampsia risk. +-*Patient Data:* Collects relevant health information, including: Age, weight, and BMI Blood pressure readings Family medical history @@ -23,3 +28,4 @@ Future Plans: Mobile Application: Develop a mobile version for wider accessibility. Continuous Model Improvement: Enhance accuracy with more diverse datasets. Integration with Wearables: Gather real-time health data from wearable devices. +