The research
we’re pursuing.
Active investigations and published work across responsible AI, precision screening, biosensing, genomics, and clinical translation.
Showing 9 research publications from all projects as a list.
- Paper
The TRIPOD-LLM reporting guideline for studies using large language models
Gallifant, J., Afshar, M., Ameen, S., et al.
An extension of the TRIPOD+AI statement providing standardized reporting guidelines for studies using large language models in healthcare — a living, modular checklist emphasizing transparency, human oversight, and task-specific performance.
Nature Medicine · 2025ToolTRIPOD+LLM - Paper
Team Card: a protocol for documenting team positionality in medical AI
Modise, LM., Alborzi Avanaki, M., Ameen, S., Celi, LA., Chen, VXY., et al.
Introduces the Team Card, a protocol for documenting research-team composition and positionality in medical AI, using reflexivity to surface and mitigate the biases teams bring to clinical systems.
PLOS Digital Health · 2024ToolTeam Card - Paper
A Framework and Assessment Models for Medical Education in the Era of Generative AI and ChatGPT
Yee, KC., Wong, MC., Ameen, S., Wylie, S.
Proposes a framework and assessment models for medical education in the era of generative AI, arguing that assessment must evaluate the process of producing work — not just the output — and that educators and students need grounding in the science behind AI.
Ottawa 2024 Conference · 2024 Improving colorectal cancer screening - consumer-centred technological interventions to enhance engagement and participation amongst diverse cohorts
Ameen, S., Wong, MC., Turner, P., Yee, KC.
Argues that persistently low colorectal cancer screening participation is best addressed through human-centered, consumer-facing technological interventions tailored to the most vulnerable cohorts.
Clinics and Research in Hepatology and Gastroenterology · 2023The Inverse Data Law: Market Imperatives, Data, and Quality in AI Supported Care
Ameen, S., Wong, MC., Yee, KC., Nøhr, C., Turner, P.
Highlights how the effectiveness of AI-augmented colorectal cancer diagnostics is constrained by low screening participation, and calls for socio-technical approaches sensitive to the psycho-social and cultural dimensions of screening.
Studies in Health Technology and Informatics · 2023AI and Clinical Decision Making: The Limitations and Risks of Computational Reductionism in Bowel Cancer Screening
Ameen, S., Wong, MC., Yee, KC., Turner, P.
Examines the computational reductionism embedded in AI systems for colorectal cancer — biased training data, narrow evaluations, and marginalised socio-technical factors — and argues for more balanced deployment and evaluation.
Applied Sciences · 2022AI Diagnostic Technologies and the Gap in Colorectal Cancer Screening Participation
Studies in Health Technology and Informatics · 2022- Paper
Intelligent Medical Case Based e-Learning System
Ameen, S., Han, S., Lin, Y., Lah, M., Kang, B.
Proposes an intelligent e-learning platform for case-based learning in medicine that immerses students in simulated real-world clinical contexts, letting them assess, diagnose, treat, and test virtual patients as they would in practice.
28th Australasian Conference on Information Systems · 2017 - Paper
Open Domain Question and Answering Framework using Wikipedia
Ameen, S., Chung, H., Han, S., Kang, B.
Explores an open-domain question-answering framework over Wikipedia's knowledgebase, combining CRF-based named-entity recognition with DBpedia property matching via string-similarity algorithms.
29th Australasian Joint Conference on Artificial Intelligence · 2016