GIKI Student Develops COVID-19 Detector using Artificial

Muhammad Aleem is almost graduate from GIKI, has come up with an AI (Artificial Intelligence) based solution for detecting Coronavirus using chest X-rays. He claims that his AI Corona detector provides results with 96% accuracy.

This news comes as a ray of hope for people that cannot afford expensive tests for the deadly virus. Coronavirus has caused the death of 6500 people worldwide and 170,000 cases overall. The pandemic has started spreading in Pakistan some days ago and has already affected nearly 200 people within the country.

While it had been found by American College of Radiology (ACR) that chest CT scans are often wont to detect COVID-19, they’re quite expensive for folk. However, chest X-rays are often done at any hospital or nearby dispensary.

Talking about his detector Aleem said, “With certificates in AI from Stanford, IBM, and DeepLearning.ai. I really like to use engineering in the medical field which motivated me to use AI (Artificial Intelligence).

I used this to diagnose COVID-19 since Pakistan doesn’t have proper resources for that. aside from this, I’m also developing robotic arms for medical surgery.”

Neural Networks, a sub-branch of AI, was wont to develop the detector. Aleem used a dataset of X-ray images of COVID-19 positive from Dr.Joseph Paul Cohen’s GitHub repository and normal cases from Kaggle to coach the system.

Neural networks learn to form decisions by assigning weights to various factors and correcting them on the idea of wrong decisions made within the process. Using the mentioned dataset, Aleem has been ready to achieve 85-90% accuracy.

More data are going to be required to form the predictions more accurate. Government agencies and medical authorities are contacted for the supply of more data.

Aleem has requested people to send him X-ray pictures of Coronavirus patients so his model is often perfected.

The more X-rays the systems has, the higher it’ll be ready to predict positive or negative cases of COVID-19.