Eva’s family is full of doctors in India, yet they were not able to interpret the illness of her grandmother, Nani. For a year, Nani had been experiencing severe chest pain, but they did not realize it was pneumonia until it was too late because of inaccessibility to the proper resources in rural India, where Nani lived.
Similarly, Anika’s grandfather—her Nana—had been experiencing chest pain for about 2 or 3 years, but since he was in a rural part of India, he did not receive the adequate care he needed. It was too late when they finally realized he had pneumonia.
Impacted by this, the four of us decided to make it easier. A lot of people in rural areas have laptops but not enough qualified people to diagnose them, and this is a major problem.
Pneumonia is fatal in 35% of hospitalized patients, meaning that the effect on non-hospitalized and untreated patients must be even more severe. Therefore, we trained a model to recognize pneumonia. Our solution can be effectively used for other illnesses and diseases as well.
One major challenge was Tensorflow not working in Replit, but we found a way to get around that.
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