MedXpert

Problem Statement

The NHS appointment system currently prioritizes patients on a first-come, first-served basis, causing critically ill patients to wait as long as those with mild issues. This approach delays essential care for severe cases, potentially worsening health outcomes. Therefore we thought that there should be a smart ML Based system to prioritize appointments based on the severity of medical conditions to ensure timely treatment for those in urgent need.

What it does /How it Works

Patient Registration:

The application begins with patient registration, where users provide information such as login details, basic personal information, and medical history. Once registered, patients can log into the application. Health Severity Assessment:

After logging in, users can perform a Health Severity Assessment. For this, they enter relevant details like age, symptoms, existing conditions, and vital measurements (e.g., body temperature, blood pressure). Upon submission, these values are sent to the server, where a trained machine learning model analyzes them and predicts the severity level of the patient's condition. Based on predicted values, the patient can now book an appointment from NHS Option

How we built it

We are using Android application to register user and collect all the information , we developed it using ReactNative , in the back end we are using Java Spring boot with REST APIS so that we can store all the values to the database and utilize them in our ML Model later on , And For the Prediction we are using Python , we have trained our model using Decision Tree Classifier

Challenges we ran into

-> In the future this Project can be integrated with NHS Application so that they can prioritize severe patients, but right now it has not been integrated to it . -> Can achieve more accuracy if the large free data set is available for training. -> Managing flow of data through network , we faced some challenges while passing data from one machine to another but fortunately it was resolved

Accomplishments that we're proud of

We believe that integrating this project with the NHS could significantly enhance the efficiency of the appointment scheduling system . Not just proposing idea , but completing it is also a big achievement for us

What we learned

We learned several ways to increase your efficiency while coding, and make things work more quickly, another major aspect is collaboration, working in a team is a skill, and its really essential throughout our career

What's next for MedXpert

We have planned Many other feature for this application , -> Disease detection system -> Health monitoring System ( Notify patients and Track their regular readings if they have any medical condition like heart disease) --> We are still planning more

Built With

• ai
• docker
• graphic-designing
• java
• javascript
• json
• machine-learning
• python
• react
• rest-api
• spring
• springweb
• sql
• sqlserver