Zeeshan Haider on Muck Rack

Zeeshan Haider

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  • News Editor, BBC Urdu, BBC
Chittagong, London
As seen in: BBC, Dailymotion, Medium, Business Insider, Daily Mail, HuffPost, Nature, Reuters, MDPI, Science Magazine, Yahoo and
News Editor BBC Urdu | @bbcurdu | Journalist in the Capital | Digital Story Teller | Avid reader, Hodophile & a Foodie | RTs≠endorsements
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Articles

Electric field–guided random-access DNA data storage

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By Youngmin Ko, John Hintze, Luise Fast, Doyeon Lim, Taeseok Kang, Wonjin Lee, Zeeshan Haider , Seunghwan Noh, Minsang Yu, Xiaohua Huang, Hyuk Soo Eun, Youngjun Song
| Science Magazine
Abstract INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS Acknowledgments Supplementary Materials REFERENCES Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract DNA offers the promise of high-density, long-term storage, yet current systems face limitations due to polymerase chain reaction–based manual workflows that are inherently slow, error prone, and difficult to scale for practical applications.
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Retraction Note: Towards improved fake news detection using a hybrid RoBERTa and metadata enhanced XGBoost model

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By Armughan Ali, Zeeshan Haider , Hooria Shahbaz, Haris Masood, Abdullah Rashid, Zahra Waheed, Jinkyung Ha, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani, Bilal Gul
| Nature
Retraction of: Scientific Reports https://doi.org/10.1038/s41598-025-29942-y, published online 04 December 2025 The Editors have retracted this Article. After publication, concerns were raised regarding the use of non‑standard vocabulary throughout the Article. An investigation by the Editors further identified multiple instances of irrelevant and misaligned references. The Editors therefore no longer have confidence in the Article.
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A Statistical and Machine Learning-Driven Framework for Predictive and Explainable Classification of Non-Invasive Blood Glucose Levels Using Photoplethysmography[v1] | Preprints.org

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By Muhammad Bilal, Haris Masood, Zeeshan Haider , Armughan Ali
| preprints.org
Submitted: 11 October 2025 You are already at the latest version Effective diabetes management requires precise non-invasive monitoring systems that surpass the limitations of traditional glucose testing.
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