Project Name: Vital Check Team Sarthak Bathla - MERN Stack developer Shivam Singh - MERN Stack developer Sumegha Gupta - MERN Stack developer Srishti Gupta - Data Scientist & Machine Learning Engineer

Roles and Contributions Sarthak Bathla: Managed project planning and developed backend functionalities. Shivam Singh: Designed and implemented the frontend interface using React.js. Sumegha Gupta: Worked on collection of data and integrated all the elements into the project. Srishti Gupta: Designed predictive models for various diseases.

Tech Used Frontend: React.js, HTML5, CSS3 Backend: Node.js, Express.js Database: MongoDB Machine Learning: TensorFlow, scikit-learn, Matplotlib, seaborn, sklearn Version Control: Git, GitHub

IDEA: Elevating Healthcare with Predictive Insights: Unveiling Health Prognosis

Goal: By giving people predicted health information, we want to transform the healthcare industry. With the use of proactive technologies, we hope to close the gap between symptom perception and medical diagnosis, enabling users to better predict and handle future health risks.

Successes: => Empowerment via Knowledge: Our technology provides users with a thorough understanding of their health state through the use of sophisticated algorithms, allowing them to make educated decisions and take preventative action. => Early Identification and Avoidance: Our software enables early illness diagnosis, enabling prompt treatments and possibly life-saving actions through symptom-based analysis and test report interpretation. => Improved Health: Through customized health evaluations and practical suggestions, consumers may develop better routines that enhance their general health and quality of life.

1)Selecting possible illnesses and answering questions about symptoms allows users to instantly determine their likelihood of being afflicted. Analysis of Test Reports:

2. The method provides probability of particular diseases mentioned in medical test findings, such as MRI or X-ray interpretations. Examining Symptoms for Unidentified Illnesses:

3. Customized questions based on the afflicted body area may be sent to users who are having symptoms but are unsure of the underlying ailment, helping to narrow down possible diagnoses. Analysis of Health and Suggestions for Improvement:

4. Daily health measurements may be recorded by users, who will then receive thorough monthly evaluations along with doable suggestions for improving their lifestyle.

In summary, Health Prognosis empowers people to take control of their health journeys by going beyond traditional healthcare paradigms. By using predictive insights to their full potential, we open the door to a world where proactive healthcare is the standard and people are happier and healthier.

CORE CODE EXPLAINATION:

=> JUPYTER NOTEBOOK: Various machine learning models are used like decision tree classifier and support vector machine to see the probability of a particular disease. Deep learning models comes in place for training process with images. The immense data set has been collected from kaggle and few other websites using scraping. Accuracy for each model has been found out. All the models provide prominient accuracy score.

=> FRONTEND AND BACKEND: We integrated model with the website. The three main features have been provided . Accordinly, the input is been taken by user and probability or a boolean value is returned .

CHALLENGES FACED: The major issue is teh data extraction and collection. TOur depen TEAM MATES DETAILS:

Sarthak Bathla :
College: Maharaja Agrasen Institute of Technology Passing Year: 2025 Current semester: 6th sem Github: https://github.com/sarthakbathla17

Shivam Singh :
College: Maharaja Agrasen Institute of Technology Passing Year: 2026 Current semester : 4th sem Github: https://github.com/shvam15

Sumegha Gupta :
College: Maharaja Agrasen Institute of Technology Passing Year: 2025 Current semester : 6th sem Github: https://github.com/04sumegha

Srishti Gupta :
College: Maharaja Agrasen Institute of Technology Passing Year: 2025 Current semester : 6th sem Github: https://github.com/srishtiiiiii5