<h1>Digital platform as a centralized medical assistant for patients in Sri Lanka.</h1>
**Main objective**
* To create a centralized mobile app for the health industry in Sri Lanka.
* Incorporating features such as symptom-based disease identification.
* Doctor recommendation and appointment system
* Utilization of medical records for disease prevention
* Generating actionable insights from long-term medication reports.
**Main Research questions**
These research problems reflect the challenges and opportunities presented in the development of the mobile app, aiming to address the current gaps in Sri Lanka's health industry.
* Limited Patient Feedback and Doctor Recommendation System
* Inadequate Utilization of Medical Records for Disease Prevention
* Insufficient Actionable Insights from Long-Term Medication Reports
**Individual research question**
Component 1: Symptom Analysis and Referral (IT20059040)
How can machine learning and natural language processing techniques be used to accurately identify diseases based on symptoms and suggest the appropriate type of physician?
Component 2: Doctor Recommendation and Appointment Booking (IT20082642)
How can patient feedback and previous medication history be leveraged to recommend the most suitable doctor and enable online appointment booking
Component 3: Medical Record Analysis and Patient Instructions(IT20033514)
How can medical records be processed and analyzed to provide accurate assessments of a patient's condition and deliver personalized instructions for disease prevention and control?
Component 4: Long-Term Medication Monitoring and Reporting (IT20075408)
How can long-term medication adherence be monitored and appropriate action be taken for patients with non-communicable diseases?
**Individual Objectives**
*Component 1: Symptom Analysis and Referral (IT20059040)*
* Develop a comprehensive database of symptoms and their corresponding diseases.
* Train a machine learning model using symptom-disease mapping data.
* Implement speech recognition or text-based input for symptom entry.
* Apply the machine learning model to analyze symptoms and provide accurate disease identification.
* Utilize a database of physician specializations to suggest the most suitable type of physician for each disease.
*Component 2: Doctor Recommendation and Appointment Booking (IT20082642)*
* Design a feedback collection system to gather patient experiences and medication history.
* Develop a recommendation algorithm that analyzes the feedback and medication history to find the best doctor match.
* Implement an online appointment booking feature that connects patients with their recommended doctors.
* Provide an intuitive user interface for patients to view doctor recommendations and schedule appointments.
* Ensure seamless integration between the recommendation system and appointment booking functionality.
*Component 3: Medical Record Analysis and Patient Instructions(IT20033514)*
* Create a system for scanning or inputting medical records into the mobile app.
* Develop machine learning algorithms to analyze medical records and extract relevant information about the patient's condition.
* Generate personalized notes and instructions based on the analysis of the medical records.
* Provide user-friendly interfaces for patients to input their medical records and access the generated notes and instructions.
* Ensure the accuracy and confidentiality of the medical record analysis process.
*Component 4: Long-Term Medication Monitoring and Reporting (IT20075408)Research Question: How can long-term medication adherence be monitored and appropriate action be taken for patients with non-communicable diseases?*
* Define a system for tracking and monitoring medication adherence on a weekly, monthly, or quarterly basis.
* Develop mechanisms to collect data on patients' medication usage and record it in the app.
* Generate regular reports summarizing medication adherence and recommending necessary actions for improvement.
* Design user-friendly interfaces for patients to view their medication reports and the corresponding recommended actions.
* Implement features that facilitate communication between patients and healthcare providers to address any concerns or issues related to long-term medication.
