Design and Development of a Medical Image Diagnosis System Based on Machine Learning

— —

Hamid Borkot Tulla, MD

Design and Development of a Medical Image Diagnosis System Based on Machine Learning

Name: Design and Development of a Medical Image Diagnosis System Based on Machine Learning
Price: 102.64 AUD
Availability: OutOfStock
ISBN: 9789999328296

Hamid Borkot Tulla, MD

$127.95 $102.64

Paperback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Eliva Press
05 December 2025

Electronics engineering; Computer science

Summary
Details

""Design and Development of a Medical Image Diagnosis System Based on Machine Learning"" by Md. Hamid Borkot Tulla is a pioneering undergraduate research project aimed at transforming breast cancer diagnosis. Leveraging the power of deep learning and transfer learning, this study deploys a fine-tuned ResNet50 convolutional neural network on the renowned BreaKHis dataset to classify histopathological breast tissue images as benign or malignant. The model achieved a remarkable accuracy of 81.28% and recall of 94.65%, providing reliable diagnostic support in clinical workflows. This research not only offers a practical AI-driven decision-support system for pathologists but also lays the groundwork for future multi-class classification models and real-time clinical integration in resource-constrained healthcare settings.

By: Hamid Borkot Tulla MD
Imprint: Eliva Press
Dimensions: Height: 229mm, Width: 152mm, Spine: 5mm
Weight: 145g
ISBN: 9789999328296
ISBN 10: 9999328296
Pages: 100
Publication Date: 05 December 2025
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active