Published Paper Details:

In the absurd situations such as lockdown or due to some urgency, busy schedule etc. Most people do not go for regular medical checkups. Even if they have certain health problems such as coughing, runny nose etc. on regular intervals they still do not prefer referring a doctor. Keeping in mind the gap between the doctors and patients, and the ability of AI to take human comparable decisions, An Application that can diagnose a person�s disease based on his/her symptoms, external doctors online feedback and consultancy, and fairly accurate Machine Learning algorithms is thought of a first step to bridge the gap between the people and the health services. Diagnosis process like many other processes is ready to be digitalized and this will all be possible because of digital system�s ability to learn using dataset, and when this process of machine learning along with a large dataset of limited diseases is used, it becomes practical to have a diagnosis without any doctor involved. And so this research paper contains the prerequisites, techniques and the past researches in this field to explain the idea and its feasibility in the practical world. This research paper also contains the working technologies of essential components of the application such as its AI engine, APIs, database, middle layers, UI, etc. Along with their most suitable form of implementation in the application, e.g.: Apache server could be used instead of SQL server that is being used but it would have required an additional middleware technology such as PHP or Java.