Digital Histopathology
Digital Histopathology
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Developing weakly supervised learning and Self-Supervised learning-based algorithms for cancer detection i.e stomach cancer, breast cancer, colon and liver cancer detection using Whole Slide Images (WSI).
We are collaborating with different hospitals and companies for this project and I am leading one of the teams for AI model development.
More than 90 researchers are working on different approaches to come up with viable solutions for automated diagnosis of cancer from whole slide images that will help expedite decision-making process for pathologists efficiently with high performance.
Covid-19 disease Prediction using X-ray images based on AI
Detection of Covid-19 and Focusing on Interpretability and Explainability of the Black Box of AI Model.
Different image processing techniques were used to improve the quality of the image.
Densely Connected Squeeze Convolutional Neural Network (DCSCNN) was proposed to classify the lungs diseases.
Describe what role you played on your team. Who did you have to work with to achieve your goal? What was the outcome of the project?
Describe what role you played on your team. Who did you have to work with to achieve your goal? What was the outcome of the project?
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