User profiles for Liam G. McCoy
Liam G. McCoy, MD MScNeurology Resident Physician, UAlberta Verified email at mail.utoronto.ca Cited by 423 |
Believing in black boxes: machine learning for healthcare does not need explainability to be evidence-based
Objective To examine the role of explainability in machine learning for healthcare (MLHC),
and its necessity and significance with respect to effective and ethical MLHC application. …
and its necessity and significance with respect to effective and ethical MLHC application. …
[HTML][HTML] What do medical students actually need to know about artificial intelligence?
With emerging innovations in artificial intelligence (AI) poised to substantially impact medical
practice, interest in training current and future physicians about the technology is growing. …
practice, interest in training current and future physicians about the technology is growing. …
[HTML][HTML] Equity in essence: a call for operationalising fairness in machine learning for healthcare
INTRODUCTION Machine learning for healthcare (MLHC) is at the juncture of leaping from
the pages of journals and conference proceedings to clinical implementation at the bedside. …
the pages of journals and conference proceedings to clinical implementation at the bedside. …
Characterizing early Canadian federal, provincial, territorial and municipal nonpharmaceutical interventions in response to COVID-19: a descriptive analysis
Background: Nonpharmaceutical interventions (NPIs) are the primary tools to mitigate early
spread of the coronavirus disease 2019 (COVID-19) pandemic; however, such policies are …
spread of the coronavirus disease 2019 (COVID-19) pandemic; however, such policies are …
[HTML][HTML] Developing and validating a prediction model for death or critical illness in hospitalized adults, an opportunity for human-computer collaboration
OBJECTIVES: Hospital early warning systems that use machine learning (ML) to predict
clinical deterioration are increasingly being used to aid clinical decision-making. However, it is …
clinical deterioration are increasingly being used to aid clinical decision-making. However, it is …
[HTML][HTML] Ensuring machine learning for healthcare works for all
LG McCoy, JD Banja, M Ghassemi… - BMJ Health & Care …, 2020 - ncbi.nlm.nih.gov
Unfortunately, modern healthcare is already rife with treatments that fail to live up to evidentiary
scrutiny, 10 while evidence behind their use is riddled with biases that further deepen …
scrutiny, 10 while evidence behind their use is riddled with biases that further deepen …
[HTML][HTML] An ethical analysis of clinical triage protocols and decision-making frameworks: what do the principles of justice, freedom, and a disability rights approach …
Background The expectation of pandemic-induced severe resource shortages has prompted
authorities to draft and update frameworks to guide clinical decision-making and patient …
authorities to draft and update frameworks to guide clinical decision-making and patient …
Large scale genotype‐and phenotype‐driven machine learning in Von Hippel‐Lindau disease
Von Hippel‐Lindau (VHL) disease is a hereditary cancer syndrome where individuals are
predisposed to tumor development in the brain, adrenal gland, kidney, and other organs. It is …
predisposed to tumor development in the brain, adrenal gland, kidney, and other organs. It is …
[HTML][HTML] MIT COVID-19 Datathon: data without boundaries
…, OJ Mechanic, J Mlabasati, LG McCoy… - BMJ …, 2021 - ncbi.nlm.nih.gov
Twitter Eva M Luo@ EvaMLuo Publisher's Disclaimer: Map disclaimer The depiction of
boundaries on the map (s) in this article do not imply the expression of any opinion whatsoever …
boundaries on the map (s) in this article do not imply the expression of any opinion whatsoever …
[HTML][HTML] Peer review of GPT-4 technical report and systems card
The study provides a comprehensive review of OpenAI’s Generative Pre-trained Transformer
4 (GPT-4) technical report, with an emphasis on applications in high-risk settings like …
4 (GPT-4) technical report, with an emphasis on applications in high-risk settings like …