Automating your doctor’s hustles and providing you with better healthcare with AI.
An open-source project for serving deep learning-based solutions in clinical scenarios. Lately, deep learning and its application in computer vision have proven to be highly beneficial for medical scenarios like Covid-19 detection, pneumonia identification, brain tumour segmentation, implant detection, etc. However, taking this work to the production side as a Minimum Value Product has been very slow. This not only reduces the far-reaching impact of the work but also diminishes the opportunities for validation by actual medical practitioners. Hence, this project is meant to serve as an end-end solution for having a web app that anyone can use for automating the diagnosis and prognosis of common problems. Initially, we plan to start with common image classification problems like Pneumonia Detection, Intracranial Hemorrhage Detection and then proceed to even more complex scenarios
Brief Description and Contents to be covered
Building a service that ensures the benefits of Artificial Intelligence reaches to medical professionals as well the common people to automate diagnosis & prognosis as well as reduce the costs, time spent and chances of human error.
Prediction of Diabetic Retinopathy using Fundus Images
Prediction of Pneumonia using Chest Radiographs (And extend to Covid-19 Detection)
Detection of Intracranial Brain Haemorrhage.
Blood Cell Classification and average count to predict the onset of blood-based diseases
Identify metastatic tissue in histopathological scans of lymph node sections for early identification of breast cancer
Abstract (2-3 lines)
Automating your doctor’s hustles and providing you with better healthcare with AI.
An open-source project for serving deep learning-based solutions in clinical scenarios. Lately, deep learning and its application in computer vision have proven to be highly beneficial for medical scenarios like Covid-19 detection, pneumonia identification, brain tumour segmentation, implant detection, etc. However, taking this work to the production side as a Minimum Value Product has been very slow. This not only reduces the far-reaching impact of the work but also diminishes the opportunities for validation by actual medical practitioners. Hence, this project is meant to serve as an end-end solution for having a web app that anyone can use for automating the diagnosis and prognosis of common problems. Initially, we plan to start with common image classification problems like Pneumonia Detection, Intracranial Hemorrhage Detection and then proceed to even more complex scenarios
Brief Description and Contents to be covered
Pre-requisites for the talk
Able to Share my screen During the event
The time required for the talk
10-15 mins
Link to slides
Link to the Powerpoint
Will you be doing a hands-on demo as well?
Just give a glance for reference.
Authors
Smaranjit Ghose Anush Bhatia
Are you comfortable if the talk is recorded and uploaded to PyData Delhi's YouTube channel?
Yes
Any query?
Timings for our event.