Faculty profile

Samira Abbasgholizadeh Rahimi

ResearcherEpidemiology, Biostatistics and Occupational HealthMcGill University

This profile is built from public research funding records (CIHR, NSERC and SSHRC) and PubMed. We have not imported them from a McGill University directory, so their courses may be missing. Find their university profile.

Samira Abbasgholizadeh Rahimi

Researcher

Epidemiology, Biostatistics and Occupational Health

Health Sciences

McGill University

Montreal, Quebec, Canada

Supervision signals

Has led research grants, which requires an independent research appointment. Ask their department whether they supervise graduate students.
34 publications in the last five years, latest in 2026.
Senior (last) author on 17 recent papers, a sign of leading a research group.
Principal investigator on 9 research grants (6 CIHR, 2 NSERC, 1 SSHRC), most recently in 2026.
Supervised 2 trainees who won CIHR awards, most recently in 2025.

These signals come from public records, including CIHR, NSERC and SSHRC funding decisions. Ask the professor or the graduate program whether they are taking new students.

Academic metrics

Publications

Citations

h-index

Collaborators

Grants

Publications by year

Counts cover the works listed on the university profile; citation counts come from Dimensions.

Profiles and links

Search on Google Scholar

Find them onX · LinkedIn · Bluesky · YouTube

Signals and details

Research

Data Management Practices Data Sharing Meta-Research Artificial Intelligence Community-Based Equity, Diversity And Inclusion (Edi)Public And Population Health Dementia Prevention

Latest papers

AI Methods for Implementation Science (AIM-IS): developing a framework, toolkit, and reporting standard for the responsible use of AI in implementation practice and research.
Implementation science : IS · 2026
Machine learning-based prediction of Metabolic Syndrome risk in the Quebec population.
BMJ digital health & AI · 2026 · senior author
The digital heartbeat: a qualitative descriptive study on women's views on preventing cardiovascular disease in primary care.
Family practice · 2026

All 40 publications

Latest funding

Deriving insights for research data sharing from a large-scale data sharing initiative in Canada
CIHR · 2026 · Principal investigator
$100,000
Bayesian Approach to Trustworthy AI for Reducing Delays in Oral Cancer Detection
CIHR · 2025 · Co-investigator
$321,300
Uncertainty Aware Large Language Models for Clinical Decision Support in Early Diagnosis of Oral Cancer.
CIHR · 2025 · Supervisor
$120,000

All 20 grants and awards

40 publications.

AI Methods for Implementation Science (AIM-IS): developing a framework, toolkit, and reporting standard for the responsible use of AI in implementation practice and research.

Fontaine G, Michie S, Beidas RS, Geng E, Fahim C, Powell BJ, Welch V, Thomas J, Chan J, Abbasgholizadeh-Rahimi S, Légaré F, Hastings J, Lambert SD, Presseau J, Straus SE, An R, Saran A, Taylor N

Implementation science : IS2026

DOI: 10.1186/s13012-026-01503-5 PMID: 41975498

Machine learning-based prediction of Metabolic Syndrome risk in the Quebec population.

Qiu H, Nejadshamsi S, Wang T, Daskalopoulou SS, Abbasgholizadeh Rahimi S

BMJ digital health & AI2026Senior author

DOI: 10.1136/bmjdh-2026-000065 PMID: 42712279

The digital heartbeat: a qualitative descriptive study on women's views on preventing cardiovascular disease in primary care.

Bousbiat IC, Abbasgholizadeh-Rahimi S, Grad R, Rodríguez C

Family practice2026

DOI: 10.1093/fampra/cmag041 PMID: 42318916

External validation of cough-based algorithms for pulmonary tuberculosis screening from the CODA TB DREAM challenge using cough data from Peru.

Zimmer AJ, Espinoza-Lopez P, Ravi V, Sieberts SK, Abbasgholizadeh Rahimi S, Pai M, Ugarte-Gil C, Grandjean Lapierre S

Scientific reports2026

DOI: 10.1038/s41598-026-50492-4 PMID: 42162050

Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation.

Nejadshamsi S, H Chu C, McGilton KS, Li X, Ronquillo C, Abbasgholizadeh-Rahimi S

JAMIA open2026Senior author

DOI: 10.1093/jamiaopen/ooaf171 PMID: 41522832

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

Zimmer AJ, Ravi V, Espinoza-Lopez P, Kafentzis GP, Ravanelli M, Abbasgholizadeh Rahimi S, Pai M, Ugarte-Gil C, Grandjean Lapierre S

Annals of epidemiology2026

DOI: 10.1016/j.annepidem.2026.110076 PMID: 41862033

Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study.

Nejadshamsi S, Karami V, Ghourchian N, Armanfard N, Bergman H, Grad R, Wilchesky M, Khanassov V, Vedel I, Abbasgholizadeh Rahimi S

JMIR aging2025Senior author

DOI: 10.2196/67715 PMID: 40053734

Tracking the Evolving Role of Artificial Intelligence in Implementation Science: Protocol for a Living Scoping Review of Applications, Evaluation Approaches and Outcomes.

Fontaine G, Di Lalla O, Michie S, J Powell B, Welch V, Thomas J, Chan J, Abbasgholizadeh-Rahimi S, Légaré F, Hastings J, D Lambert S, Presseau J, E Straus S, D Graham I, An R, N Elakpa D, Mooney M, Matra Putra AD, Laritz R, Taylor N

F1000Research2025

DOI: 10.12688/f1000research.171774.2 PMID: 41835982

Family caregivers' acceptance of Artificial Intelligence-enabled technologies for providing care to older adults.

Yee A, Yaffe MJ, Schuster T, Lambert S, Abbasgholizadeh-Rahimi S

BMC geriatrics2025Senior author

DOI: 10.1186/s12877-025-06249-1 PMID: 41469851

Are Machine Learning methods effective in detecting undiagnosed atrial fibrillation in primary care settings using electronic health records? A systematic review.

Chalati MD, Shirvankar C, Gore G, Sharma A, Abbasgholizadeh-Rahimi S

PLOS digital health2025Senior author

DOI: 10.1371/journal.pdig.0001009 PMID: 41086202

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their CIHR grant from 2026

Subject: Prospective PhD student: Data Management Practices Dear Professor Abbasgholizadeh Rahimi, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "AI Methods for Implementation Science (AIM-IS): developing a framework, toolkit, and reporting standard for the responsible use of AI in implementation practice and research." (2026), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your CIHR-funded project "Deriving insights for research data sharing from a large-scale data sharing initiative in Canada" (2026), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]

Something wrong or missing on this profile? Suggest a correction

Samira Abbasgholizadeh Rahimi

Research

Latest papers

Latest funding

AI Methods for Implementation Science (AIM-IS): developing a framework, toolkit, and reporting standard for&#xa0;the responsible use of AI in implementation practice and research.

Machine learning-based prediction of Metabolic Syndrome risk in the Quebec population.

The digital heartbeat: a qualitative descriptive study on women's views on preventing cardiovascular disease in primary care.

External validation of cough-based algorithms for pulmonary tuberculosis screening from the CODA TB DREAM challenge using cough data from Peru.

Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation.

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study.

Tracking the Evolving Role of Artificial Intelligence in Implementation Science: Protocol for a Living Scoping Review of Applications, Evaluation Approaches and Outcomes.

Family caregivers' acceptance of Artificial Intelligence-enabled technologies for providing care to older adults.

Are Machine Learning methods effective in detecting undiagnosed atrial fibrillation in primary care settings using electronic health records? A systematic review.

Frequent collaborators

Dan Poenaru

Pierre Pluye

Howard Bergman

Marie-Pierre Gagnon

Elham Emami

Simon Grandjean Lapierre

Simon Grandjean Lapierre

Isabelle Vedel

Guillaume Fontaine

Maxime Sasseville

Elif Bilgic

Madhukar Pai

Vivian Welch

Elham Emami

Isabelle Vedel

Justin Presseau

Machelle Wilchesky

Anne Bourbonnais

Vladimir Khanassov

Yves Couturier

Amal Idrissi Janati

Pascaline Kengne Talla

Sreenath Madathil

Kathleen Leslie

Sylvie Lambert

Sathya Karunananthan

Amanda Grenier

Christine Fahim

Nadia Sourial

Abhinav Sharma

Guillaume Fontaine

Nadia Sourial

Jean-Claude Forest

Charlene Chu

Julie Lane

Clare Liddy

Amanda M Grenier

Patrick Archambault

Meredith Young

Tibor Schuster

AI Methods for Implementation Science (AIM-IS): developing a framework, toolkit, and reporting standard for the responsible use of AI in implementation practice and research.