Mohammad Ashrafuzzaman
4 Papers
Mohammad Ashrafuzzaman is an academic researcher. The author has contributed to research in topics: Cross-sectional study & Feature selection. The author has an hindex of 1, co-authored 2 publications.
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Papers
IoT Intrusion Detection Using Machine Learning with a Novel High Performing Feature Selection Method
Khalid Albulayhi,Qasem Abu Al-Haija,Suliman A. Alsuhibany,Ananth Abhishek Jillepalli,Mohammad Ashrafuzzaman,Frederick T. Sheldon +5 more
TL;DR: A novel feature selection and extraction approach for anomaly-based IDS that is superior and competent with a very high 99.98% classification accuracy is proposed and compared with other state-of-the-art studies.
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir,Aasa Feragen,Abdul Joseph Fofanah,Alejandro F. Frangi,Alena Buyx,Anais Emelie,Andrea Lara,Antonio R. Porras,An-Wen Chan,Arcadi Navarro,Ben Glocker,Benard Ohene Botwe,Bishesh Khanal,Brigit Beger,Carol C Wu,Celia Cintas,Curtis P. Langlotz,Daniel Rueckert,Deogratias Mzurikwao,Dimitrios I. Fotiadis,Doszhan Zhussupov,Enzo Ferrante,Erik Meijering,Eva Weicken,Fabio A. Gonz'alez,Folkert W. Asselbergs,Fred Prior,Gabriel P. Krestin,Gary S. Collins,Geletaw Sahle Tegenaw,Georgios Kaissis,Gianluca Misuraca,Gianna Tsakou,Girish Dwivedi,Haridimos Kondylakis,Harsha Jayakody,Henry C Woodruf,H. J. Aerts,Ian Walsh,Ioanna Chouvarda,Irène Buvat,Islem Rekik,James Duncan,Jayashree Kalpathy–Cramer,Jihad Zahir,Jinah Park,John Mongan,Judy Wawira Gichoya,Julia A. Schnabel,Kaisar Kushibar,Katrine Riklund,Kensaku Mori,Kostas Marias,Lameck M. Amugongo,Lauren A. Fromont,Lena Maier-Hein,Leonor Cerd'a Alberich,Leticia Rittner,Lighton Phiri,Linda Marrakchi-Kacem,Lluis Donoso-Bach,L. Mart'i-Bonmat'i,M. Jorge Cardoso,Maciej Bobowicz,Mahsa Shabani,Manolis Tsiknakis,Maria A. Zuluaga,Mária Bieliková,Marie-Christine Fritzsche,Marius George Linguraru,Markus Wenzel,Marleen de Bruijne,Martin G. Tolsgaard,Marzyeh Ghassemi,Mohammad Ashrafuzzaman,Melanie Goisauf,Mohammad Yaqub,Mohammed Ammar,M'onica Cano Abad'ia,Mukhtar M. E. Mahmoud,Mustafa Elattar,Nicola Rieke,Nickolas Papanikolaou,Noussair Lazrak,Oliver D'iaz,O. Salvado,Oriol Pujol,Ousmane Sall,Pamela Guevara,P.M. Gordebeke,Philippe Lambin,Pieta Brown,Purang Abolmaesumi,Qi Dou,Qinghua Lu,Richard Osuala,Rose Nakasi,S. K. Zhou,Sandy Napel,Sara Colantonio,Shadi Albarqouni,Smriti Joshi,Stacy Carter,Stefan Klein,Steffen E. Petersen,Susanna Auss'o,Suyash P. Awate,Tammy Riklin Raviv,Tessa S. Cook,Tinashe Mutsvangwa,Wendy A Rogers,Wiro J. Niessen,Xènia Puig-Bosch,Yi Zheng,Yunusa G Mohammed,Yves Saint James Aquino,Zohaib Salahuddin,Martijn P. A. Starmans +117 more
TL;DR: The FUTURE-AI guideline is described as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare and provides a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice.
Ensembling Supervised and Unsupervised Machine Learning Algorithms for Detecting Distributed Denial of Service Attacks
Saikat Das,Mohammad Ashrafuzzaman,Frederick T. Sheldon,Sajjan Shiva +3 more
TL;DR: This study proposes an ensemble-based machine learning approach combining supervised and unsupervised methods to detect DDoS attacks, achieving up to 99.1% accuracy with negligible false alarms on three benchmark datasets.
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Knowledge and awareness of infection control practices among nursing professionals: A cross-sectional survey from South Asia and the Middle East
Kanwalpreet Sodhi,Gunjan Chanchalani,Muktanjali Arya,Juhi Chandwani,Manender Kumar,Monika Gulati Kansal,Mohammad Ashrafuzzaman,Anushka Dilani Mudalige,Ashraf Al Tayar,Bassam Mansour,Madiha Hashmi,Mitul Das,N. Al Shirawi,Ranjan Mathias,Wagih Ouda Ahmed,Amandeep Sharma,D. Agarwal,Prashant Nasa +17 more
TL;DR: In this article , an online self-assessment questionnaire based on various aspects of infection prevention and control (IPC) practices was conducted among nurses over three weeks, and a significant association was found between the knowledge and expertise of nurses, the country's percapita income, type of hospitals, accreditation and teaching status of hospitals and type of ICUs.