Cojinsky
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Medical machine learning
A project to detect multiple human diseases through symptom analysis
Disease diagnosis expert system using pyke
This Knowledge Expert System uses PyKnow/Experta to provide medical advice and basic knowledge of diseases based on symptoms
This is a python implementation of a rule based knowledge based system that can diagnose a couple diseases.
This project aims to build a handy software, that would help users to diagnose certain diseases like heart disease, and covid-19 with maximum possible accuracy.
This project uses Machine learning and Information Retrival techniques to detect diseases based on symptoms.
This is an app which can be used to diagnose diseases in less than 30 seconds. The app uses simple decision tree algorithm coded from scratch. The app is able to predict more than 130 diseases.
A medical expert system that helps diagnose the diseases and prescribe appropriate medication
Classification and Segmentation: Diagnose diseases from x-rays and 3D MRI brain images. Predict patient survival rates more accurately using tree-based models. Estimate treatment effects on patient…
An app hosted using Streamlit and uses the Decision Tree Classifier to suggest top 10 diseases based on the symptoms entered by the user.
This app will interactively ask the user about the symptoms, which he is facing and then it will predict the disease of the user using the concept of decision trees. Also, this code is run on a dat…
A knowledge infused Context driven (KI-CD) Disease Diagnosis VA
I worked on a TinyML application powered by Edge Impulse to develop a mini-Diagnosis ECG analyzer device which can fit on a pocket and it can diagnose heart diseases independently without an Internet.
Simple expert system which provides medical diagnosis for common ailments
Electron-based Medical Healthcare System, which provides diagnosis on the basis of symptoms.
Medical Diagnosis App with Decision tree ML model
CNN to diagnose heart disease in ECG and MCG patients