Nazmus Shakib on Muck Rack

Nazmus Shakib

As seen in: Medium, Nature, openPR
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Nazmus

Contact Nazmus, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Towards trustworthy brain stroke diagnosis using a lightweight explainable deep learning framework for CT imaging

|
By Chayan Mondal, Nazmus Shakib, Ahsan Habib, KAMRUL HASAN, Romzan Alom, Muhammad Aminur Rahaman, Parvez Hossain, A. B. M. Shawkat Ali
| Nature Verified
Abstract Brain stroke occurs due to blockage or rupture in the cerebral blood supply and represents a critical medical emergency requiring rapid and accurate diagnosis. However, manual interpretation of CT scans is time-consuming and may delay clinical decision-making. To address this challenge, this study proposes the Deep Neural Brain Stroke Detection (DNBSD) system, a lightweight deep learning–based framework for automated stroke detection from CT images.
Open in Who Shared Issue with article?

Computer Science > Machine Learning

|
By Nazmus Shakib, Aaron Cummings, Xinyue Zhang
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (412) Issue with article?

Computer Science > Machine Learning

|
By Nazmus Shakib, Xinyue Zhang, Jingyi Wang
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (518) Issue with article?
See all 8 articles
 •  Privacy  •  Terms  •  Security and Legal  •   •   •   • 

© 2026 Muck Rack

SOC 2® Certified