The problem HomeCare.ai solves

• Whenever a patient visits a hospital it takes a significant amount of time before the updated health reports of the patient
  arrives making it difficult for the proper detection and hence decision making for the health official.

• Also, it has now become unsafe to go to the hospital every time we feel unwell, since there is a risk of getting affected by
  COVID 19. The pandemic has caused an influx in hospital cases, and the limitations on hospital beds have people wondering
  whether their symptoms are severe enough to warrant a doctor's appointment.

• Meanwhile, others experience ailments but are unable to afford a visit to the doctor due to a lack of proper health care.
  Further, if the patient recognizes his/her symptoms, and if somehow we can tell him what is the disease he is likely to be
  affected with then accordingly precautions can be taken at home only.

• Since, everyone should have easy access to great health care there is a need to connect patients virtually with doctors in an
  efficient manner.

• In a digital world affected by COVID 19, telemedicine is more necessary than ever to improve the quality and accessibility of
  medical care to distant users and also improve the decision making process of clinicians as well as help people know what
  disease they are likely to be infected with and what precautionary measures can be taken with the help of Artificial
  Intelligence.

• So we have designed a solution deployable in a healthcare setting that can help to improve the quality and accessibility of
  medical care facilities to distant users, help in the remote diagnosis of patients by connecting them remotely to the doctors around the globe in an efficient manner, disease detection through analysis of symptoms followed by proper precautions and drug recommendations, provided mutli-disease computer aided diagnosis system, supports lab test appointment facilities, patient health management and also aid in the decision making process of doctors.

Challenges we ran into

• Improving the efficiency of the trained machine and deep learning models on different diseases. To tackle this, we collected data from the open source platform kaggle and used various hyper parameter techniques such as random search, AutoML, augmentations, dropouts, early stopping etc, which led to better accuracy of all the models.
• Connect patients remotely with the doctors over video call. For this, we used dailyJS API to provide a video call feature.