To access our application you can either download the android application.
X-rays are a commonly used diagnostic tool in medical settings. They are used to visualize the internal structure of the body and help doctors diagnose various diseases and conditions. However, the interpretation of X-rays can be challenging and requires a high level of expertise. Misinterpretation of X-rays can lead to misdiagnosis and delay in treatment, resulting in further complications.
To address this issue, DiagnoX was developed to assist doctors in interpreting X-rays. It uses advanced machine learning algorithms to analyze X-rays and provide a preliminary diagnosis. This preliminary diagnosis is presented to the doctor, who can then confirm or modify it based on their own expertise.
To develop app for medical professionals who have a limited amount of time to review and analyze X-ray or MRI scans, which can lead to misdiagnosis or missed diagnoses. Improving the traditional methods of generating reports for X-ray or MRI scans can be time-consuming and labor-intensive. To help the patients in remote or underserved areas may have difficulty accessing healthcare services, including the expertise needed to analyze X-ray or MRI scans.
To address this issue, DiagnoX was developed to assist doctors in interpreting X-rays. It uses advanced machine learning algorithms to analyze X-rays and provide a preliminary diagnosis. This preliminary diagnosis is presented to the doctor, who can then confirm or modify it based on their own expertise.
DiagnoX is designed to be highly user-friendly, with a simple interface that can be easily integrated into a hospital's existing system. The system is also highly customizable, allowing doctors to modify the algorithms and criteria used for diagnosis based on their preferences.
- Get diagnosed X-Rays with pre-diagnosis through deep-learning model
- Get prognosis and chances if you can die in the next 10 years or not through official hospital reports.
- Get recommendation for users to visit nearby doctors.
- Easy to understand Minimilastic and Interactive UI/UX Design
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React Native, Python, Flask, Tensorflow, GCP, Git, Numpy, Pandas, Scikit, Matplotlib Technologies : Deep Learning, DenseNet121
Clone the repo in your local machine and setup python and flutter environment. Create .env file similar to .env.sample file with all the required fields.
- Go into
app/directory by doingcd appin terminal. - Configure firebase for android by folllowing the doumentation.
- Write
flutter runin the terminal to start the application.
- Install all the required packages in python virtual enviroment
pip install -r requirements.txt - Run
python app.pyin the root directory of the project.