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Mourad Bouache
Sunnyvale, California
Lung disease AI Classifier
Radiology mistakes form 4% of medical errors, which cause many dangerous effects on patients health including deaths. This project aims to develop an Artificial Intelligence tool that will assist doctors and radiologists to detect and classify lung diseases in order to prevent diagnosis errors. ...learn more
Project status: Under Development
Groups
SkaiLab,
Student Developers for AI
Intel Technologies
Other
Overview / Usage
Radiology mistakes form 4% of medical errors, which cause many dangerous effects on patients health, including deaths. This project aims to develop an Artificial Intelligence tool that will assist doctors and radiologists in reading x-ray images, in order to prevent diagnosis errors, by classifying and detecting the lungs diseases , it is able to :
- Differentiate between a healthy lung and a sick one (from X-Ray images)
- Detect the diseased area
- Make a diagnosis (classification)
Methodology / Approach
We use Deep Learning to classify lung diseases, the project will detect the diseased area in the x-ray image of the person and then classify into: Healthy lung , Pneumonia, Tuberculosis (until now)
Technologies Used
Keras , tensorflow , intel OpenVINO, Intel Xeon CPU, Intel AI Analytics Toolkit (Intel OneAPI) , intel optimization Tensorflow , and intel distribution for python