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Special Session
Special Session on
Machine Learning and Deep Learning Improve Preventive and Personalized Healthcare
 - Cognitive Health IT 2020

24 - 26 February, 2020 - Valletta, Malta

Within the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSTEC 2020


Tahir Hameed
Organization and Analytics, Merrimack College
United States

Brief Bio
Tahir Hameed obtained his Ph.D. in Information Technology Management from the Korea Advanced Institute of Science and Technology (KAIST), and obtained his Masters in Computer Science from Lahore University of Management Sciences (LUMS). He is a Visiting Associate Professor for management information systems with Merrimack College since 2018. Hameed was also a faculty member at SolBridge International School of Business in South Korea from 2012 to 2018. Dr. Hameed’s current research focuses on health analytics particularly clinical decision support systems and consumer health informatics, IT standards, IT adoption and technology innovation and commercialization.
Syed Ahmad Chan Bukhari
St. John's University
United States

Brief Bio
Dr. Bukhari is an Assistant Professor and Director of Healthcare Informatics at St. John's University, New York. He received his Ph.D. in Computer Science from the University of New Brunswick, Canada, and completed his postdoctoral fellowship at Yale University. He was also a core research team member at CEDAR Metadata Center, Stanford University. With the Stanford team, he studied scientific experimental reproducibility and completed several projects to improve biomedical data FAIRness and reproducibility. Dr. Bukhari received NIH (ORISE) NCBI fellowship in 2016 to work at National Center for Biotechnology Information (NCBI), Bethesda. Dr. Bukhari developed protocols and pipelines (MiAIRR, CAIRR, and CEDAR-to-NCBI ) for the standardized authoring, validating, and submitting scientific data to the NCBI repositories with NCBI Scientists. His developed resources are now considered de facto resources for several biomedical communities such as AIRR-C & Antibody society. At St. John's University, he teaches healthcare Informatics and computer science to graduate and undergrad students. His current research efforts focus on addressing several core problems in healthcare informatics and data science. Dr. Bukhari has received multiple internal and external grants to support his research efforts.


Machine learning has transformed healthcare by improving disease prediction, diagnosis, prognosis, and treatments. Using large but relatively structured datasets like electronic health records (EHRs), scans, and labs, they provide indispensable tools and decision support to healthcare providers and patients. Lately, with bigger, more complex and unstructured datasets available, healthcare apps and clinical decision support systems (CDSS) have started to leverage deep learning to refine these recommendations. Such systems not only have prediction but learning capabilities also. Consequently, they enable preventive and rehabilitative healthcare that is highly personalized and adaptive. This session seeks completed research on applications of deep learning and cognitive computing in preventive care, personalized treatments and adaptive CDSS aiming to better health outcomes, patient satisfaction and costs.

Topics of Interest
Topics of interest include, but are not limited to:
  • Machine Learning
  • Deep learning and Cognitive Computing approaches in Disease Prediction
  • Diagnosis
  • Prognosis
  • Personalized Treatments
  • Clinical Decision Support Systems (CDSS)
  • Adaptive CDSS
  • Precision Medicine and more to enhance preventive and adaptive healthcare


Paper Submission: December 28, 2019 (expired)
Authors Notification: January 9, 2020 (expired)
Camera Ready and Registration: January 17, 2020 (expired)


Qasim Bukhari, 80 Newbury Avenue, Apt 5, Massachusetts Institute of Technology, United States
Safee U. Chauhdry, Biology, Lahore University of Management Sciences, Pakistan
Hasan Ali Khattak, Computer Science, National University of Sciences and Technology (NUST), Pakistan
Ikram Ullah Lali, University of Gujrat, Pakistan
Syed Qasim Bukhari, Massachusetts Institute of Technology, United States
Rana Zia Ur Ur U. Rehman, Newcastle University, United Kingdom
Amnah Siddiqa, Department of Medicine, Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Emory University School of Medicine, United States
Bobby Swar, Concordia University of Edmonton, Canada


Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.


After thorough reviewing by the special session program committee, all accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on digital support - and submitted for indexation by DBLP, Web of Science / Conference Proceedings Citation Index, EI, SCOPUS, Microsoft Academic, Semantic Scholar and Google Scholar.
SCITEPRESS is a member of CrossRef ( and every paper is given a DOI (Digital Object Identifier).
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library


BIOSTEC Special Sessions - Cognitive Health IT 2020