© Design Innovation All Rights Reserved
Meet the Team
Mentors: Dr. Prashant Jindal, Dr. Mamta Juneja
Project interns: Vishal Kumar Singh, Riya Gupta, Sahiba Uppal, Prachi Gaur, Shantanu Gautam, Shubh Vishvas, Ramneek Kaur, Apoorva, Diksha Mahajan, Harleen Kaur, Jatinder Kaur, Ojaswani
Introduction: SWASTHYA: DISEASE DIAGNOSIS APP.
Problems:
It becomes difficult for doctors to analyze a large amount of data manually and predict the disease, the process is tiresome.
The identification and diagnosis of such diseases at their earlier stages are much more important, so as to prevent the extremity of it.
Motive:
To deliver a medical-grade ML-powered disease diagnosis application to aid doctors in the early disease detection in case of Cardiovascular disease, Liver Cirrhosis, Kidney Corioliss.
Features:
It is used to predict the diseases like kidney Corioliss, heart attack, liver cirrhosis. It is based on machine learning and involves using historical medical data, such as patient symptoms, lab results, and medical history, to train a model to predict the likelihood of a patient having a certain disease. Create a highly accurate model in predicting disease status, which could potentially be used in clinical settings to aid in diagnosis.
The application would likely involve a combination of data preprocessing, feature selection, and model training and evaluation.
Provide assurance to doctors by reducing their manual diagnostic hours.
Semi and fully automated and less error-prone.
Accurate results without the help of specialists.
Low-cost and easily accessible diagnosis to help millions of people worldwide.
Technology Stack
- Primary coding language:
- 1) Python
- Other libraries and tools used:
- 1) Matplotlib
- 2) sci-kit learn
- 3) Streamlit
- 4) Kivy
- 5) Pandas
- 6) Numpy
Information
- Name of the Department: UIET, Panjab University
- Name of Project: Design Innovation Centre(DIC)
- Name of Group : Medical Devices and Restorative
Technologies (MDaRT)
