Work with thought leaders and academic experts in Health Information Management

Companies can benefit from collaborating with academic researchers in Health Information Management in several ways. These experts can help enhance data management systems, improve healthcare outcomes, provide valuable insights for decision-making, develop innovative solutions, and contribute to research and development efforts. By partnering with these researchers, companies can stay ahead of industry trends, ensure compliance with regulations, optimize processes, and leverage cutting-edge technology. Additionally, collaboration with academic researchers can lead to knowledge transfer, networking opportunities, and access to funding and grants.

Researchers on NotedSource with backgrounds in Health Information Management include Christos Makridis, Gwendolyn Thomas, Ph.D., CSCS, USAW-L1, Jim Samuel, Dr. Aalok Thakkar, Atefeh Abdolmanafi, Ph.D., Carissa Clark, Bernd Stahl, Sheraz Ch, Xander van Wijk, PhD, DABCC, FADLM, Kayvan Najarian, Syed Ishtiaque Ahmed, and Asif Khan.

Christos Makridis

Nashville, TN
10 Years Experience
Web3 and Labor Economist in Academia, Entrepreneurship, and Policy
Education

Stanford University

Dual Ph.D., Economics and Management Science & Engineering / June, 2018

Stanford, California, United States of America

Arizona State University

B.S., Economics and Mathematics / May, 2012

Tempe, Arizona, United States of America
Experience

Stanford University

Digital Fellow / August, 2020 — Present

Department of Veterans Affairs

Senior Adviser, National AI Institute / January, 2020 — Present

Columbia Business School

Adjunct Associate Research Scholar / February, 2022 — Present

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (15)
Finance
Economics and Econometrics
Accounting
Pharmacology (medical)
Law
And 10 more
About
Christos A. Makridis holds academic appointments at Columbia Business School, Stanford University, Baylor University, University of Nicosia, and Arizona State University. He is also an adjunct scholar at the Manhattan Institute, senior adviser at Gallup, and senior adviser at the National AI Institute in the Department of Veterans Affairs. Christos is the CEO/co-founder of [Dainamic](https://www.dainamic.ai/), a technology startup working to democratize the use and application of data science and AI techniques for small and mid sized organizations, and CTO/co-founder of [Living Opera](https://www.livingopera.org/), a web3 startup working to bridge classical music and blockchain technologies. Christos previously served on the White House Council of Economic Advisers managing the cybersecurity, technology, and space activities, as a Non-resident Fellow at the Cyber Security Project in the Harvard Kennedy School of Government, as a Digital Fellow at the Initiative at the Digital Economy in the MIT Sloan School of Management, a a Non-resident Research Scientist at Datacamp, and as a Visiting Fellow at the Foundation for Defense of Democracies. Christos’ primary academic research focuses on labor economics, the digital economy, and personal finance and well-being. He has published over 70 peer-reviewed research papers in academic journals and over 170 news articles in the press. Christos earned a Bachelor’s in Economics and Minor in Mathematics at Arizona State University, as well a dual Masters and PhDs in Economics and Management Science & Engineering at Stanford University.
Most Relevant Publications (2+)

25 total publications

Ethical Applications of Artificial Intelligence: Evidence From Health Research on Veterans

JMIR Medical Informatics / Jun 02, 2021

Makridis, C., Hurley, S., Klote, M., & Alterovitz, G. (2021). Ethical Applications of Artificial Intelligence: Evidence From Health Research on Veterans. JMIR Medical Informatics, 9(6), e28921. https://doi.org/10.2196/28921

Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs

BMJ Health & Care Informatics / Jun 01, 2021

Makridis, C. A., Strebel, T., Marconi, V., & Alterovitz, G. (2021). Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs. BMJ Health & Care Informatics, 28(1), e100312. https://doi.org/10.1136/bmjhci-2020-100312

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Gwendolyn Thomas, Ph.D., CSCS, USAW-L1

Philadelphia, Pennsylvania, United States of America
17 Years Experience
Resistance Exercise Physiologist/Performance Enhancement/Optimizing RE Prescription
Education

University of Connecticut

Ph.D., Kinesiology (Exercise Endocrinology, Exercise Physiology, Resistance Exercise) / May, 2010

Storrs, Connecticut, United States of America

University of Connecticut

M.A., Strength and Conditioning / May, 2007

Storrs, Connecticut, United States of America
Experience

Penn State University

Assistant Research Professor / September, 2019 — August, 2023

Principal Investigator of the Exercise Prescription Lab. The lab (PI: Thomas) conducts interdisciplinary and translational research on chronic diseases, publishing in peer-reviewed journals. Transform population health outcomes through data, analytics, and actionable insights. Chair the regulatory review board, overseeing IRB Administration, running meetings, and approving research protocols. Expertise in institutional, FDA, and Federal regulatory work.

Penn State Integrative Physiology

Faculty Member / September, 2019 — Present

Faculty Member In Integrative Physiology

Syracuse University

Assistant Professor / August, 2016 — August, 2019

Independent Principal Investigator: Assumed responsibility for all research studies conducted in my lab, including but not limited to oversight and training of research assistants (25), training of research assistants (30), and generating independent, high quality, reproducible results. Responsible for the management and integrity of design, conduct and reporting of the research project and for managing, monitoring and ensuring the integrity of collaborative relationships. Curriculum Committee Chair:Led Curriculum Committee and Departmental Leadership to develop Master’s Degree in Strength and Conditioning through certifying agency, the National Strength and Conditioning Association (NSCA).

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (30)
resistance exercise
obesity
breast cancer
chronic disease
inflammation
And 25 more
About
My work has focused on how we can use data to support decisions to individualize monitoring to optimize human performance.  My work has demonstrated that a one size fits all approach is not the way to optimize performance in any setting.  My monitoring approach is one that utilizes a network physiology paradigm, which focuses on nonlinear dynamic interactions. In my athlete monitoring I focus on leveraging EMA and wearables; biological sampling and resistance exercise and conditioning prescribed to elicit a specific biological response.    Additionally, as a practitioner it is important to understand the limitations of athlete monitoring, which is another area research and practice has focused.  This is an important skillset that is currently being utilized by the in a project entitled “Integrating mHealth and Physical Function to Develop a Predictors of Injury and Optimal Performance Model in Special Military Operators “with the Rangers in the 3/75 Ranger Battalion.  This approach is one that quantifies factors such as dosage variables of training and lifestyle factors (sleep, nutrition, life stress).  Using this data, we are working on individualizing acute training sessions to optimize readiness and performance enhancement.   During my time at Syracuse University, I was the professor of record to teach the NSCA CSCS preparation course and lead the strength and conditioning program.  We were developing a master’s in exercise science and I was in the process of working on certification with the NSCA.  We also worked closely with athletics to secure strength and conditioning assistantships to allow for student funding.  I am currently on several NSCA committees, which include the Education and Women’s Committee (next certification cycle).    I am particularly adept at all phases of the athletic performance enhancement and these experiences have given me expertise in evidence based program design, linear and non-linear periodization, exercise endocrinology, resistance exercise physiology and acute and chronic training readiness and non-training parameters
Most Relevant Publications (1+)

51 total publications

Qualitative analysis addressing physician-perceived barriers to usage of electronic patient questionnaires in a colorectal clinic

Journal of Communication in Healthcare / Sep 25, 2014

Solomon, E. R., Thomas, G., & Gurland, B. (2014). Qualitative analysis addressing physician-perceived barriers to usage of electronic patient questionnaires in a colorectal clinic. Journal of Communication in Healthcare, 7(3), 208–213. https://doi.org/10.1179/1753807614y.0000000059

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Jim Samuel

11 Years Experience
Associate Professor at Rutgers University
Education

Baruch College

PhD, Information Systems / 2007

New York, New York, United States of America
Experience

Rutgers University

Associate Professor / 2021 — Present

Axivest

CIO / 2012 — Present

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (21)
Analytics
Artificial Intelligence
Informatics
Machine Learning
NLP NLU NLG Behavioral Finance
And 16 more
About
Jim Samuel is an Associate Professor of Practice and Executive Director of the Informatics Program at the Bloustein School. He is an information and artificial intelligence (AI) scientist, with significant industry experience in finance, technology, entrepreneurship and data analytics. Dr. Samuel’s primary research covers human intelligence and artificial intelligences interaction and information philosophy.  Dr. Samuel’s applied research focuses on the optimal use of big data and smart data driven AI applications, textual analytics, natural language processing and artificially intelligent public opinion informatics. His expertise extends to socioeconomic implications of AI, applied machine learning, social media analytics, AI education and AI bias. Dr. Samuel completed his Ph.D. from the Zicklin School of Business, Baruch College – City University of New York, and he also has M.Arch and M.B.A (International Finance) degrees.  Dr. Samuel has worked with large multinational financial services corporations, and advises businesses and organizations on data analytics and AI driven value creation strategies. He is passionate about research driven thought leadership in AI, information philosophy, analytics and informatics. 
Most Relevant Publications (1+)

44 total publications

Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics

Healthcare / Aug 27, 2021

Ali, G. G. Md. N., Rahman, Md. M., Hossain, Md. A., Rahman, Md. S., Paul, K. C., Thill, J.-C., & Samuel, J. (2021). Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics. Healthcare, 9(9), 1110. https://doi.org/10.3390/healthcare9091110

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Dr. Aalok Thakkar

Seattle, Washington, United States of America
1 Years Experience
Research Scientist focussed on integrating formal methods and artificial intelligence.
Education

Chennai Mathematical Institute

Bachelor's of Science, Mathematics

Siruseri

University of Pennsylvania

Ph.D., Computer and Information Science / May, 2023

Philadelphia, Pennsylvania, United States of America
Experience

Movement Labs

Research Engineer / February, 2024 — Present

Aptos Labs

Research Scientist / July, 2023 — January, 2024

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (8)
programming languages
verification
logic
synthesis
Computer Science Applications
And 3 more
About
My research focuses on integrating **formal methods** and **artificial intelligence**. In particular, I have worked on applying formal methods in the context of programming-by-examples (PBE) for relational queries, synthesis of reactive programs, bounded model checking, and verification of smart contracts. Currently, I work with Movement Labs on designing the Fractal interpreter will allow users to deploy Solidity smart contracts directly on Movement's M1 blockchain. Previously, I have worked with Aptos Labs, Amazon AWS, Nokia Bell Labs, and Adobe India.
Most Relevant Publications (1+)

12 total publications

Reopening businesses and risk of COVID-19 transmission

npj Digital Medicine / Mar 16, 2021

O’Donoghue, A., Dechen, T., Pavlova, W., Boals, M., Moussa, G., Madan, M., Thakkar, A., DeFalco, F. J., & Stevens, J. P. (2021). Reopening businesses and risk of COVID-19 transmission. Npj Digital Medicine, 4(1). https://doi.org/10.1038/s41746-021-00420-9

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Atefeh Abdolmanafi, Ph.D.

15 Years Experience
Ph.D. in Computer Science with publications on Medical AI
Education

Ph.D., Computer Science (Artificial Intelligence) / May, 2014

Montreal, Quebec, Canada

Master of Science, Applied Physics/ Solid State Physics / January, 2009

Tehran

Bachelor of Science, Applied Physics / June, 2005

Hamedan
Experience

ViTAA Medical Solutions

Senior Research Scientist / August, 2020 — August, 2023

 Designed an automatic system to recognize and extract aortic tissues in abdominal aortic aneurysms (AAAs) using deep learning models. A patent application was filed for this study in February 2020.  Developed an automated system for pre-interventional planning and post-interventional monitoring of endovascular aortic repair using machine learning and deep learning models. A patent application was submitted for this study in October 2021.  Designed a machine learning-based model to incorporate image information into AAA growth prediction. A patent application was filed for this study in October 2022.

Université du Québec (École de technologie supérieure)

Research Assistant / June, 2019 — August, 2020

 Analyzed intraluminal coronary arteries, including the automatic detection of red thrombus, white thrombus, and residual blood.  Quantified the coronary arterial wall by automatically detecting pathological tissues, particularly calcification, macrophage accumulation, neovascularization, atheroma, lipid, and endothelial fibrosis, to prevent cardiac adverse events.

Polytechnique Montreal

Postdoctoral fellow / June, 2018 — June, 2019

 Created a computer-aided diagnostic framework that provides clinicians with operator-independent diagnoses of histological coronary lesions.  Conducted volumetric assessments of different coronary artery tissues to evaluate their dynamics and functionality.  Estimated the elasticity of coronary artery tissues affected by coronary artery disease (CAD) to assess the dynamics and functionality of the arterial wall.

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (12)
Pattern recognition
Medical image analysis
Machine learning
Deep learning
Biotechnology
And 7 more
About
Throughout my research journey, I have demonstrated a commitment to advancing the field of medical imaging and artificial intelligence (AI) applications in healthcare. Starting with my master's program in physics, where I specialized in optical phenomena, I built a strong foundation in imaging principles that laid the groundwork for my subsequent research endeavors. My doctoral work focused on coronary artery tissue characterization for pediatric patients with Kawasaki Disease, utilizing innovative approaches such as Convolutional Neural Networks and 3D reconstruction techniques. This work garnered international recognition, culminating in a presentation at the 12th International Symposium on Kawasaki Disease in Japan. During my postdoctoral fellowship, I led the development of a groundbreaking computer-aided diagnostic framework, addressing a critical need in healthcare and presenting at prestigious conferences. Transitioning to industry, I joined Aligo Innovation to bridge the gap between academia and industry applications, successfully contributing to technology transfer and business development. In collaboration with ViTAA Medical Solutions, I played a pivotal role in developing an automated system for analyzing computed tomography images in abdominal aortic aneurysms, resulting in filed patents and impactful publications. More recently, I have taken on a more active role in academia, mentoring students, collaborating on innovative projects, and launching the "MedTech Innovations Journal (MIJ)" to bridge technology and healthcare. Beyond my research pursuits, I am a passionate advocate for the synergy of art and science, as reflected in my book "Being Fully Connected" and recent art exhibitions in Toronto and Montreal. My multifaceted background underscores my dedication to pushing the boundaries of knowledge and creativity in the intersection of technology and healthcare.
Most Relevant Publications (1+)

9 total publications

Intra-Slice Motion Correction of Intravascular OCT Images Using Deep Features

IEEE Journal of Biomedical and Health Informatics / May 01, 2019

Abdolmanafi, A., Duong, L., Dahdah, N., & Cheriet, F. (2019). Intra-Slice Motion Correction of Intravascular OCT Images Using Deep Features. IEEE Journal of Biomedical and Health Informatics, 23(3), 931–941. https://doi.org/10.1109/jbhi.2018.2878914

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Carissa Clark

9 Years Experience
Associate Professor at Saint Louis University
Education

University of California, Los Angeles

Ph.D., Social Welfare / July, 2012

Los Angeles, California, United States of America
Experience

Saint Louis University

Associate Professor of Family and Community Medicine / February, 2015 — Present

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (33)
poverty
mental health
substance abuse
Applied Psychology
Psychiatry and Mental health
And 28 more
About
Carissa van den Berk Clark, Ph.D., LMSW, is an associate professor of family and community medicine. Prior to joining the department, she received her Ph.D. in social welfare policy from the Luskin School of Public Affairs at UCLA where she also completed a pre-doctoral training at the West Los Angeles Veterans Affairs. She was also a NIDA postdoctoral fellow at the Washington University School of Medicine, Department of Psychiatry. Currently, she is a RWJ IRL fellow, as well as outreach and communications director for the SLU ARCHNet practice based research network and the deputy director of the SLU Area Health Education Center. Her research focuses heavily on substance abuse, mental health, care coordination and uses community participatory methodology.
Most Relevant Publications (2+)

69 total publications

Three Types of Intimate Relationships among Individuals with Chronic Pain and a History of Trauma Exposure

Healthcare / Sep 29, 2017

van den Berk-Clark, C., Weaver, T., & Schneider, F. (2017). Three Types of Intimate Relationships among Individuals with Chronic Pain and a History of Trauma Exposure. Healthcare, 5(4), 68. https://doi.org/10.3390/healthcare5040068

Differences in the Association between Depression and Opioid Misuse in Chronic Low Back Pain versus Chronic Pain at Other Locations

Healthcare / Jun 16, 2016

Jaiswal, A., Scherrer, J., Salas, J., van den Berk-Clark, C., Fernando, S., & Herndon, C. (2016). Differences in the Association between Depression and Opioid Misuse in Chronic Low Back Pain versus Chronic Pain at Other Locations. Healthcare, 4(2), 34. https://doi.org/10.3390/healthcare4020034

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Bernd Stahl

36 Years Experience
Director of the Centre for Computing and Social Responsibility
Education

De Montfort University

DSc, Centre for Computing and Social Responsibility

Leicester

De Montfort University

LLM in Business Law / October, 2007

Leicester

University Witten / Herdecke

PhD, Philosophy and Economics / November, 2002

Witten
Experience

University of Nottingham

Professor of Critical Research in Technology / October, 2022 — Present

De Montfort University

Director / June, 2003 — September, 2023

University College Dublin

Lecturer in Information Systems / September, 2000 — March, 2003

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (52)
critical theory
information systems
computer ethics
information ethics
responsible innovation
And 47 more
Most Relevant Publications (1+)

145 total publications

Who is Responsible for Responsible Innovation? Lessons From an Investigation into Responsible Innovation in Health Comment on "What Health System Challenges Should Responsible Innovation in Health Address? Insights From an International Scoping Review"

International Journal of Health Policy and Management / May 19, 2019

Stahl, B. C. (2019). Who is Responsible for Responsible Innovation? Lessons From an Investigation into Responsible Innovation in Health Comment on “What Health System Challenges Should Responsible Innovation in Health Address? Insights From an International Scoping Review.” International Journal of Health Policy and Management, 8(7), 447–449. https://doi.org/10.15171/ijhpm.2019.32

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Sheraz Ch

8 Years Experience
1DANA Brain Health Institute, Iranian Neuroscience Society-Fars Chapter, Shiraz, Iran 2Senses Cultural Foundation, Sacramento, CA, USA
Education

University of Eastern Finland

Masters in Public Health (MPH) / December, 2014

Kuopio

Baqai Medical University

Doctor of Pharmacy (PharmD) / April, 2011

Karachi
Experience

University of Tasmania, Australia

PhD Research Scholar / March, 2020 — Present

Ministry of Health

Head of Scientific and Staff Development / July, 2019 — February, 2020

Researcher / November, 2015 — February, 2020

London School of Hygiene and Tropical Medicine

Co-investigator, CRASH-3 Study / May, 2016 — September, 2017

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (15)
Neuroimaging
Machine learning
Brain disorder
Deep learning
Brain signal processing
And 10 more
Most Relevant Publications (1+)

15 total publications

Awareness of Cardiovascular Disease Risk Factors by Community Pharmacists in Saudi Arabia

Healthcare / Jan 04, 2023

Sulaiteen, F. M., Al-Zaagi, I. A., Alenazi, M. S., Alotaibi, A. Z., Alghamdi, T. A., Yousaf, A., & Ali, S. (2023). Awareness of Cardiovascular Disease Risk Factors by Community Pharmacists in Saudi Arabia. Healthcare, 11(2), 151. https://doi.org/10.3390/healthcare11020151

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Xander van Wijk, PhD, DABCC, FADLM

Strategic Leader in Clinical Diagnostics | Expert in Laboratory and Precision Medicine | Award-Winning Scientist & Author | CLIA Laboratory Director
Most Relevant Research Expertise
Health Information Management
Other Research Expertise (40)
Clinical Chemistry
Cardiac Biomarkers
Analytical Toxicology
Pharmacogenomics
Blood Gas
And 35 more
About
A leader in the field of laboratory and precision medicine, passionate about improving healthcare through innovative solutions. Well versed in working in regulated environments (CLIA, FDA). Holding multiple board and leadership positions. Strong track record of scientific contributions with 70+ peer-reviewed articles, book chapters, and (inter)national podium presentations. Received several recent major awards & recognitions.
Most Relevant Publications (1+)

59 total publications

Counterfeit Norco Poisoning Outbreak — San Francisco Bay Area, California, March 25–April 5, 2016

MMWR. Morbidity and Mortality Weekly Report / Apr 29, 2016

Vo, K. T., van Wijk, X. M. R., Lynch, K. L., Wu, A. H. B., & Smollin, C. G. (2016). Counterfeit Norco Poisoning Outbreak — San Francisco Bay Area, California, March 25–April 5, 2016. MMWR. Morbidity and Mortality Weekly Report, 65(16), 420–423. https://doi.org/10.15585/mmwr.mm6516e1

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Kayvan Najarian

Professor of Comp Med and Bioinf, Emergency Med, and Electrical and Comp Engineering
Education

University of British Columbia

Ph.D., Electrical and Computer Engineering / August, 2000

Vancouver, British Columbia, Canada
Experience

University of Michigan, Ann Arbor

Professor

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (48)
biomedical inforamtics
bioinformatics
singal processing
image processing
machine learning
And 43 more
Most Relevant Publications (6+)

106 total publications

Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome

IEEE Journal of Biomedical and Health Informatics / Jan 01, 2019

Reamaroon, N., Sjoding, M. W., Lin, K., Iwashyna, T. J., & Najarian, K. (2019). Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome. IEEE Journal of Biomedical and Health Informatics, 23(1), 407–415. https://doi.org/10.1109/jbhi.2018.2810820

Motion Artifact Suppression in Impedance Pneumography Signal for Portable Monitoring of Respiration: An Adaptive Approach

IEEE Journal of Biomedical and Health Informatics / Mar 01, 2017

Ansari, S., Ward, K. R., & Najarian, K. (2017). Motion Artifact Suppression in Impedance Pneumography Signal for Portable Monitoring of Respiration: An Adaptive Approach. IEEE Journal of Biomedical and Health Informatics, 21(2), 387–398. https://doi.org/10.1109/jbhi.2016.2524646

A hierarchical expert-guided machine learning framework for clinical decision support systems: an application to traumatic brain injury prognostication

npj Digital Medicine / May 07, 2021

Farzaneh, N., Williamson, C. A., Gryak, J., & Najarian, K. (2021). A hierarchical expert-guided machine learning framework for clinical decision support systems: an application to traumatic brain injury prognostication. Npj Digital Medicine, 4(1). https://doi.org/10.1038/s41746-021-00445-0

Adaptive Real-Time Removal of Impulse Noise in Medical Images

Journal of Medical Systems / Oct 02, 2018

HosseinKhani, Z., Hajabdollahi, M., Karimi, N., Soroushmehr, R., Shirani, S., Najarian, K., & Samavi, S. (2018). Adaptive Real-Time Removal of Impulse Noise in Medical Images. Journal of Medical Systems, 42(11). https://doi.org/10.1007/s10916-018-1074-7

A Novel Tropical Geometry-Based Interpretable Machine Learning Method: Pilot Application to Delivery of Advanced Heart Failure Therapies

IEEE Journal of Biomedical and Health Informatics / Jan 01, 2023

Yao, H., Derksen, H., Golbus, J. R., Zhang, J., Aaronson, K. D., Gryak, J., & Najarian, K. (2023). A Novel Tropical Geometry-Based Interpretable Machine Learning Method: Pilot Application to Delivery of Advanced Heart Failure Therapies. IEEE Journal of Biomedical and Health Informatics, 27(1), 239–250. https://doi.org/10.1109/jbhi.2022.3211765

Learning Using Partially Available Privileged Information and Label Uncertainty: Application in Detection of Acute Respiratory Distress Syndrome

IEEE Journal of Biomedical and Health Informatics / Mar 01, 2021

Sabeti, E., Drews, J., Reamaroon, N., Warner, E., Sjoding, M. W., Gryak, J., & Najarian, K. (2021). Learning Using Partially Available Privileged Information and Label Uncertainty: Application in Detection of Acute Respiratory Distress Syndrome. IEEE Journal of Biomedical and Health Informatics, 25(3), 784–796. https://doi.org/10.1109/jbhi.2020.3008601

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Syed Ishtiaque Ahmed

University of Toronto
Education

Cornell University

PhD, Computer and Information Science

Ithaca
Experience

University of Toronto

Most Relevant Research Expertise
Health Information Management
Other Research Expertise (28)
HCI
ICTD
Responsible AI
Sustainability
Applied Psychology
And 23 more
Most Relevant Publications (2+)

160 total publications

A data-driven validation of mobile-based care (mCARE) project for children with ASD in LMICs

Smart Health / Dec 01, 2022

Rabbani, M., Haque, M. M., Dipal, D. D., Zarif, M. I. I., Iqbal, A., Schwichtenberg, A., Bansal, N., Soron, T. R., Ahmed, S. I., & Ahamed, S. I. (2022). A data-driven validation of mobile-based care (mCARE) project for children with ASD in LMICs. Smart Health, 26, 100345. https://doi.org/10.1016/j.smhl.2022.100345

Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach

JMIR Medical Informatics / Jun 08, 2021

Haque, M. M., Rabbani, M., Dipal, D. D., Zarif, M. I. I., Iqbal, A., Schwichtenberg, A., Bansal, N., Soron, T. R., Ahmed, S. I., & Ahamed, S. I. (2021). Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach. JMIR Medical Informatics, 9(6), e29242. https://doi.org/10.2196/29242

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Asif Khan

Researcher
Most Relevant Research Expertise
Health Information Management
Other Research Expertise (31)
Data Science
ML with Python
AI
Robot Vision
Pharmacology
And 26 more
About
### I am a highly accomplished individual with a strong educational background, having completed my Postdoc and PhD from UESTC, along with an MTech and MCA from Aligarh Muslim University (AMU). I have received multiple awards for my academic achievements, including the Excellent Research Award and the Academic Achievement Award. My expertise lies in the fields of Data Science and Robot Vision, and I am also a proficient Abroad Education Guide, Career Counselor, and Protectional Developer Trainer. I have helped numerous individuals achieve their career goals by providing personalized guidance and sharing my knowledge and experience. My passion for research and development has led me to publish several papers in renowned international journals. With my extensive skills and expertise, I am committed to empowering individuals and organizations in achieving their full potential.
Most Relevant Publications (1+)

79 total publications

IIMFCBM: Intelligent Integrated Model for Feature Extraction and Classification of Brain Tumors Using MRI Clinical Imaging Data in IoT-Healthcare

IEEE Journal of Biomedical and Health Informatics / Oct 01, 2022

Haq, A. U., Li, J. P., Agbley, B. L. Y., Khan, A., Khan, I., Uddin, M. I., & Khan, S. (2022). IIMFCBM: Intelligent Integrated Model for Feature Extraction and Classification of Brain Tumors Using MRI Clinical Imaging Data in IoT-Healthcare. IEEE Journal of Biomedical and Health Informatics, 26(10), 5004–5012. https://doi.org/10.1109/jbhi.2022.3171663

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Example Health Information Management projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on Health Information Management?

Data Management System Enhancement

An academic researcher in Health Information Management can collaborate with a company to enhance their data management system. By analyzing existing systems, identifying gaps, and implementing best practices, the researcher can help the company streamline data collection, storage, and analysis processes, leading to improved efficiency and accuracy.

Healthcare Outcome Improvement

Collaborating with an academic researcher in Health Information Management can help a company improve healthcare outcomes. The researcher can analyze healthcare data, identify patterns and trends, and provide insights on how to optimize treatment plans, reduce readmission rates, and enhance patient satisfaction.

Decision-Making Support

Companies can benefit from the expertise of academic researchers in Health Information Management to support decision-making processes. These researchers can analyze data, conduct market research, and provide evidence-based recommendations to help companies make informed decisions regarding product development, marketing strategies, and resource allocation.

Innovative Solution Development

Academic researchers in Health Information Management can collaborate with companies to develop innovative solutions. By leveraging their knowledge of emerging technologies, data analytics, and healthcare systems, these researchers can help companies create new products, services, or processes that address industry challenges and meet customer needs.

Research and Development Contribution

Collaborating with academic researchers in Health Information Management allows companies to contribute to research and development efforts. By partnering with these experts, companies can support studies, trials, and experiments that advance the field and lead to new discoveries, technologies, and treatments.