Cancer Diagnosis Has Evolved as a Frontline Area for Showcasing AI Capabilities in Healthcare

Cancer Diagnosis Has Evolved as a Frontline Area for Showcasing AI Capabilities in Healthcare

Deepak Garg 29/07/2020 4
Cancer Diagnosis Has Evolved as a Frontline Area for Showcasing AI Capabilities in Healthcare

Artificial intelligence (AI) is encompassing every paradigm of life and affecting us in one way or another.

Companies, researchers and investors always remain on the lookout for high impact interventions that bring useful transformation in society. Cancer diagnosis has recently evolved as one such area which is getting a lot of attention from everyone involved in healthcare-related AI. It makes a lot of business sense also as billions of dollars are invested in cancer-related research, medicine and applications. The number of research papers being published in this area has increased multiple times in recent years.

It makes a lot of difference to the cancer patient if the cancer is diagnosed at an early stage. This time difference in diagnosis can change the whole trajectory of the treatment. It can also alter the outcome and also save the patient from incurring significant costs on the oncological interventions required.

AI has proved to be a very useful tool due to various reasons. Now, we have a greater number of digitized images due to advancements in the field of radiology. More and more hospitals are coming forward to collaborate with AI scientists to work on those images and help advance the field of a cancer diagnosis. Computer Vision, object detection and multi-classification capabilities of AI has made it a right fit for early diagnosis of different type of cancer. It also helps incorrectly and precisely diagnosing the grade, volume, and area of the malignancy.

In 2017, Kaggle hosted a lung nodule classification and detection competition, which helped to further grow the interest of developers and scientists in this direction. The current state of the art model built by Google can predict lung cancer better than humans and increase survival rates. After that there has been a lot of such competitions including breast cancer detection, tumor volume segmentation, neck cancer lymph nodes using CT-Scans. Convolutional neural networks has become a major success tool and is able to bring the diagnostic accuracy of up to 90%.

In 2020, we have many more areas of oncological research that are in the final stages of their experimentation and will be used by different leading hospitals in their day to day functioning in the coming years. This includes the work on prostrate cancer, cervical cancer and finding low-grade glioma using brain MRIs. Biotechnology industry has also started collaborating the AI scientists to increase the innovation in drug development and biomarker discovery.

IBM Watson for Oncology has already proved itself as a good enabler for doctors in few areas for making recommendations. Recently there has been a lot of developments in multiple hospitals and technology industries collaborating from different continents to make universally acceptable models in cancer care.

With all the developments in the field, we can say, that AI is not going to replace doctors soon, but it is helping doctors to make better and early decisions. Current challenges in this field are explainability of AI, lack of proper laws and framework in place for safety, lack of Legal framework for protecting patients and doctors from the pitfalls of AI.

NVIDIA-Bennett Research Center on AI in Bennett University is also contributing to this area of research. Many research groups are working with different AI healthcare startups to solve interesting problems for society. It includes decoding the prescription written by doctors, which is generally not too easy to read and integrating it with other Hospital systems. Currently, 200 Interns from different premium institutions of the country are doing their summer internship and trying to solve open challenges on AI available on Kaggle, Innocentive, Data-driven, Chahub, Opened, Grand-Challenge, and Codalab, etc. Two groups working on Skin Cancer Classification and MRI White Matter Reconstruction challenge and have shown considerable progress.

Computer Science Department of Bennett University has established itself as a leader in AI skilling and research. It is now mentoring 1000+ institutions through its program. It is making its mark through high-quality publications, funded research, and innovative experiential teaching-learning pedagogy.

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  • Louise N

    Just thinking about bad diseases makes me shake.

  • Carl Parkin

    God help those who have cancer.

  • Paul Hunter

    Cancer is a horrible condition people don’t deserve.

  • Simon Auker

    Respect to the computer science department of Bennett University

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Deepak Garg

Tech Expert

Deepak is a Professor and Department Head of Computer Science and Engineering at Bennett University, Greater Noida. He is also a chief consultant for, a resource for algorithms. Deepak is considered as one of the best Algorithm Gurus in India. His active research interests are designing efficient deep learning algorithms. He is Senior Member of IEEE, Senior Member of ACM and Life Member of CSI, IETE. He served as chair of IEEE Computer Society, India Council from 2012-2016 and on the Board of governors of IEEE Education Society, USA (2013-15). He previously worked as a Software Engineer in IBM Corporation Southbury, CT, USA. Deepak has 100+ publications in various International Journals and conferences with 500+ citations and Google h-index of 13. In his 20 years of experience, he has delivered 200+ invited talks across India. He is an ABET PEV and serves on ABET criteria review committee of Computing Accreditation Commission. He is also an active blogger in the Times of India with the tag name of “Breaking Shackles” and is passionate about transforming the landscape of Higher Education. For more details about his accomplishments: Deepak holds a PhD in Computer Science and Engineering from Thapar University.

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