Authors

Inspiration

Recently, I saw a Developed ML model for Rapid Detection of Pneumonia by X-Ray Images. Accuracy of That  Model was 92.46%

What it does

ML Model will detect the patient’s condition whether patient is positive or negative, than the person is prompted to consult a doctor.
Currently we will trained our model on available data.  we can develop for Public if we get real life data or we deploy this system in hospitals, test Centres.

How I built it

  • The developed hack is worked upon X-Ray Images/Video.
  • ML Model will detect the patient’s condition whether patient is positive or negative, than the person is prompted to consult a doctor.
  • Currently we will trained our model on available data.
  • we can develop for Public if we get more real life data or we deploy this system in hospitals, test Centres.

Challenges I ran into

  • We simply don’t have enough (reliable) data to train a COVID-19 detector.
  • I am not a trained medical expert. It can improved by more medical expert's guidance.
  • COVID-19 detectors will be multi-modal
  • Right now i am using only image data (i.e., X-rays) — better automatic    COVID-19 detectors should leverage multiple data sources  not limited to just images, including patient vitals, population density, geographical location, etc. Image data by itself is typically not sufficient for these types of applications.

Try It out

Hackathons

Technologies

python

Devpost Software Identifier

261087