Welcome to the i4Health Research lab
@ York University
@ Vector Institute
Our Mission!
Insight for Health (i4Health) Research Lab is dedicated to addressing complex challenges influencing human health
Our Goal!
to improve the quality of care and experience for patients
to reduce the burden on health workers, and
to deliver insight and tools for policymakers
How...
We build a Fair Multimodal Pathway to improve human health
Our team delivers innovative AI solutions for healthcare that encompass scientific contributions to the STEM field and applied benefits to the healthcare system
Research Themes (ML + Health)
Our lab's focus revolves around three core themes:
Generative and Multimodal Learning using Foundation Models,
Deep Causal Discrimination Discovery
Ambient Intelligence for Good
Generative & Multimodal Learning
Deep Causal Discrimination Discovery
Ambient Intelligence 4 Good
Our lab is actively involved in various application domains stemming from these three themes, including i4PCC (insight for Post COVID Condition), i4MentalHealth,
News
Jan. 2024 - Our lab is delighted to welcome three new brilliant members, Noor Qaiser, Mansoure Jahanian, and Yasaman Parhizkar.
Oct. 2023 - Our recent research, “Vision-based detection and quantification of maternal sleeping position,” has been recently published in PLoS Digital Health;
Sep 2023 - we have an open Research Internship position in Machine Learning and Bio-informatics (to be appointed at UHN): Job posting link and @UHN ;
Sep 2023 - Our recent collaborative work with @TELUS, @DeloitteCanada & @RocheCanada, “Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: NLP Approach” has been recently published in @jmirpub
June 2023 - Our lab received collaborative seed funding for the project Machine Learning for Post-Covid Condition in collaboration with York University, GEMINI, and LongCovid Web.
June 2023 - Congratulations to Allan Kember on successfully defending his Master's thesis
May 2023 - Our lab received NSERC Discovery Grant for the project titled "Deep Multimodal Learning for Healthcare: Towards Building Multimodal Pathway Health Networks".
May 2023 - Our paper on using NLP for clinical laboratory Data Repository Systems is published at JMIR AI
April 2023 - Congratulations to Sina Akbarian on his new IEEE access paper on evaluating knowledge transfer in NN for medical images.
Feb 2023 - Our paper on diagnosing harmful data shift is now available on medrxiv
Joining the Lab (Open Positions)
Thank you for your interest in working with us. We are constantly seeking individuals who are motivated and possess exceptional talent. We are committed to promoting Equity, Diversity, and Inclusion (EDI) in our lab and strongly encourage individuals from diverse backgrounds to apply.
Are you interested in ML for Health? Are you enthusiastic about playing a vital role in advancing the ongoing revolution in the field of Machine Learning for Health? Our lab is seeking highly motivated individuals; we have the following positions available:
Graduate Students for Fall 2024 at the School of Health Policy & Management (Faculty of Health) and also jointly with Lassonde School of Engineering at York
Research Interns
Postdoctoral Fellow
Research Volunteer, Practicum, Capstone Project, or Degree Research Paper
Research Internship in Machine Learning and Bio-informatics (to be appointed at UHN): Job posting link and @UHN ; (CLOSED)
If you're interested in joining our team and wish to be contacted, kindly complete this Google form.
https://forms.gle/JLCqQb3LDbqf1wEWA
Email us:
If you are interested in collaborating with us or would like to obtain further information about our research projects, please do not hesitate to reach out to us at edolatab{AT}yorku{.}ca .