| Idea Name: |
Medical Report Diagnosis |
| Slogan: |
It's saves time that saves lives |
| Supervisor Name: |
Ms. Jaweria Hafeez |
| Supervisor Designation: |
Lecturer |
| Supervisor School: |
Other |
| Supervisor Department: |
Computer Science |
| Contact number: |
3338222147 |
| Email ID: |
[email protected] |
| Abstract: |
| This project is about diagnosing a patient’s medical report using machine learning and converting that report into easily understandable text for patients and our project focuses on providing the users immediate and accurate prediction of the disease based on their detailed analysis of their pathology reports. This application allows you to understand your health condition. |
| What is the unmet need in society that your idea will fulfill ? |
| There is a significant need in our society to empower our patients to understand their health conditions by understanding their medical test reports. In this busy world, it's difficult to get an appointment with a doctor and get your test reports diagnosed. Early diagnoses of disease can save lives. |
| Who needs it ? How many would benefit ? |
| Our patients need it the most as it will empower them to understand their medical test reports and predict the disease by detailed analysis of their medical reports. It also helps doctors and radiologists to understand test reports by just scanning test reports in a few seconds |
| How will the solution works |
| This project is about diagnosing a patient’s medical report using machine learning and converting that report into easily understandable text for patients through the encoder-decoder model with Attention mechanism in which the encoder receive sequence from the text report that is "findings" as input and produces a compact representation of the input sequence then the output becomes an input to the decoder, then decoder predicts the output that is "predicted disease" using Attention mechanism |
| Who are your competitors ? How is your solution different |
| Currently, we have no competitors and there is an essential need in our society to empower our patients to understand their health conditions. |
| Status: |
new |
| Entry Date & Time: |
2021-12-22 (1847) |
