Скачать или смотреть Liver disease prediction using Ensemble Technique | Python Final Year IEEE Project

Liver disease prediction using Ensemble Technique | Python Final Year IEEE Project.
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🔗Email: [email protected],
🌐Website: https://www.jpinfotech.org

📌IEEE Base Paper Title: Liver disease prediction using Ensemble Technique.
💡Implementation Code: Python.
🚀Algorithm / Model Used: Gradient Boosting Classifier + AdaBoost Classifier (Ensemble Technique).
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.3000/.

📘Project Abstract:
👉In recent decades, liver diseases have risen to prominence as one of the world's top causes of death and a condition that can be fatal. According to the WHO, chronic diseases are responsible for over 59 percent of global mortality and 46% of conditions, and they claim the lives of almost 35 million people worldwide.
👉This project's need is to outline a framework for an iterative method of finding high-risk patients' events that is based on a clinical data repository and machine learning algorithm.
👉Damage to the liver, which performs a vital function for the body, could have catastrophic repercussions. Early liver disease detection is crucial for this reason.
👉This work attempted to predict liver disease using an ensemble technique (Gradient Boosting Classifier + AdaBoost Classifier) based on various clinical data collected from healthy blood donors and liver patients.

📌REFERENCE:
Sai Rohith Tanuku, Addike Ajay Kumar, Sai Roop Somaraju, Rushitaa Dattuluri, Madana Vamshi Krishna Reddy, Sambhav Jain, “Liver disease prediction using Ensemble Technique”, 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS), IEEE Conference, 2022.

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#liverdisease