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<!DOCTYPE html>
<html lang="en">
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<meta charset="utf-8">
<title>Video Compilation Page</title>
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<h1>A Web Application for particular Medical Diagnostics</h1>
<p>Today's world is burdened with a lot of diseases to be taken care of as well be knowlegeable about. While doctors are at work to handle these, today's technology is capable of sharing at least a bit of their burden. This is one such small-scale attempt.</p>
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<h2>Background review to get started with the project</h2>
<p>In this informative webinar, the presenters from Criterion Edge, including Lori Mitchell and Dr. Sarah Chavez, delve into the systematic literature review process and its critical role in achieving IVDR (In Vitro Diagnostic Regulation) readiness. They emphasize the importance of conducting methodologically sound literature reviews to support regulatory requirements and strategic organizational decisions in the medical and pharmaceutical fields. The webinar outlines practical guidance, including how to design search strategies, screen literature, and extract relevant data, while also reinforcing the necessity of documenting the process for transparency and reproducibility.</p>
<iframe
src = "https://www.youtube.com/embed/watch?v=xPpOB8bSfS4"
width = "560"
height = "320"
title = "Literature Review for the project">
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<h2>Collection of Legible Datasets</h2>
<p>In this video, viewers are introduced to the essentials of data basics and collection within the context of quality improvement (QI) in healthcare. The presentation emphasizes the importance of both qualitative and quantitative data, explaining how valid and reliable measurements can illustrate changes in processes and systems. Key themes include understanding how to set appropriate measures, selecting data collection methods, and ensuring the analysis leads to sustainable improvements. The video encourages a data-driven approach to enact meaningful change in healthcare practices.</p>
<iframe
src = "https://www.youtube.com/embed/watch?v=5kKUsxg1YiA"
width = "560"
height = "320"
title = "Data collection for the project">
</iframe>
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<h2>Training ML models for the respective datasets for diagnosis for the selected diseases</h2>
<p>In this video, Siddharthan guides viewers through the process of building a multiple disease prediction system using machine learning and deploying it as a web application with Streamlit in Python. The tutorial covers various aspects including setting up the environment, saving trained models, uploading datasets, and creating a user interface for predictions on diabetes, Parkinson's disease, and other illnesses. Viewers are encouraged to follow along and build their own systems while leveraging prior videos on similar topics.</p>
<iframe
src = "https://www.youtube.com/embed/watch?v=8Q_QQVQ1HZA"
width = "560"
height = "320"
title = "Training ML Models">
</iframe>
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Build a Video Compilation Page - Build a Video Compilation Page