A transfer learning with structured filter pruning approach for improved breast cancer classification on point-of-care devices


A significant progress has been made in automated medical diagnosis with the advent of deep learning methods in recent years. However, deploying a deep learning model for mobile and small-scale, low-cost devices is a major bottleneck. Further, breast cancer is more prevalent currently, and ductal carcinoma being its most common type. Although many machine/deep learning methods have already been investigated, still, there is a need for further improvement.

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Publication: Computers in Biology and Medicine

Publisher: Science Direct

Authors: Tejalal Choudhary,  Vipul Mishra, Anurag Goswami and Jagannathan Sarangapani

Keywords: Deep learning, deep learning method, carcinoma

Meet one of the Author:

Tejalal Choudhary

Dr Tejalal Choudhary received his Ph.D. in Computer Science Engineering from Bennett University in Greater Noida, India. He has expertise in computer vision, machine learning, deep learning, and model compression. His exceptional ability to think creatively, tackle problems from multiple angles, and generate innovative solutions sets him apart from others.


Bennett University, Greater Noida, India – Bennett University was established in the year 2016 by the Times Group which is India’s largest media conglomerate, to provide Ivy League quality education to undergraduate and postgraduate students. The six schools with 30+ programs and 70+ leading specialisations in Engineering, Management, Media, Law and Liberal Arts have positioned it as one of the top universities in India.

Missouri University of Science and Technology – Missouri University of Science and Technology (Missouri S&T) is a world-class technological research university. Founded in 1870 as one of the first technological schools west of the Mississippi, Missouri S&T offers a broad array of degrees in engineering, the sciences, business, information technology, the humanities and liberal arts, and education — all in an environment that emphasizes technological literacy.

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