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A new smartphone app ,,can provide 'smart reports' that may predict the user's risk of diseases and expose hidden disorders based on their symptoms and lifestyle inputs.

Healthcare industry has become big business. The healthcare industry produces large amounts of health-care data daily that can be used to extract information for predicting disease that can happen to a patient in future while using the treatment history and health data.

This hidden information in the healthcare data will be later used for affective decision making for patient’s health. Also, this area need improvement by using the informative data in healthcare.

The app, allows users to log their basic body vitals like blood pressure, weight and sugar levels as well as maintain a depository of all their test reports for future reference.

The app then analyses the data for abnormal parameters, and recommends the future course of required action, including suitable medical specialist to consult and additional tests, if needed.

"With pathology checkups, understanding a medical report and its implications on one's health has always been a challenge," .

"With our app, this difficulty is addressed and people can now at a click of a button get deep insights into their health,". The smart report feature helps uncover latent diseases and predict risk of future ones and to expose any latent ones.

Major challenge is how to extract the information from these data because the amount is very large so some data mining and machine learning techniques can be used.

It recommends lifestyle and dietary changes based on the user's investigations, symptoms and lifestyle inputs. Patients will be able to review their medical conditions and reach their treatment goals much faster, dramatically lowering the risks of serious health complications.

Also, the expected outcome and scope of this project is that if disease can be predicted than early treatment can be given to the patients which can reduce the risk of life and save life of patients and cost to get treatment of diseases can be reduced up to some extent by early recognition.

"The smart report is meant to empower users with a fore- knowledge of possible health risks and to effectively manage chronic diseases,"

"Any decision regarding our health is best taken in an informed manner. our app is exactly that channel of reliable information," .

Diseases are predicted based on the patients' health check-up report values of different parameters along with their age, lifestyle habits, symptoms and family medical history. Along with symptoms we take lifestyle habits, age, gender and patients medical history into account to eliminate the chances of making a wrong diagnosis.

For this problem, a probabilistic modeling and deep learning approach will train a Long Short-Term Memory (LSTM) recurrent neural network and two convolutional neural networks for prediction of disease. The rapid adoption of electronic health records has created a wealth of new data about patients, which is a goldmine for improving the understanding of human health.

The above method is used to predict diseases using patient treatment history and health data.

To ensure any such misinterpretations, free doctor and dietician consultation is provided. We give a clear disclaimer to the user that these are system generated recommendations only. For an accurate diagnosis, user is encouraged to visit a particular specialist.