Errol Colak




Dr. Errol Colak is a radiologist, Project Investigator at the Li Ka Shing Knowledge Institute of St. Michael’s Hospital, and Assistant Professor in the Department of Medical Imaging, University of Toronto. His research interests include machine learning in medical imaging, genitourinary and gastrointestinal imaging, and quality improvement initiatives.

Please note: Dr. Colak is not taking any summer students.

Recent Publications

  1. Benhabib, H, Crivellaro, PS, Osman, H, Gunaseelan, S, Chung, A, Lee, JY et al.. Standardized Reporting on the Preoperative CT Assessment of Potential Living Renal Transplant Donors: Can We Create a Universal Report Standard to Meet the Needs of Transplant Urologists?. Can Assoc Radiol J. 2023; :8465371231153828. doi: 10.1177/08465371231153828. PubMed PMID:36718778 .
  2. Gaube, S, Suresh, H, Raue, M, Lermer, E, Koch, TK, Hudecek, MFC et al.. Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays. Sci Rep. 2023;13 (1):1383. doi: 10.1038/s41598-023-28633-w. PubMed PMID:36697450 PubMed Central PMC9876883.
  3. Meaney, C, Das, S, Colak, E, Kohandel, M. Deep learning characterization of brain tumours with diffusion weighted imaging. J Theor Biol. 2023;557 :111342. doi: 10.1016/j.jtbi.2022.111342. PubMed PMID:36368560 .
  4. Brassil, M, Li, Y, Ordon, M, Colak, E, Vlachou, P. Infection complications after transrectal ultrasound-guided prostate biopsy: A radiology department's experience and strategy for improvement. Can Urol Assoc J. 2022;16 (11):E523-E527. doi: 10.5489/cuaj.7781. PubMed PMID:35704931 PubMed Central PMC9665316.
  5. Salehinejad, H, Kitamura, J, Ditkofsky, N, Lin, A, Bharatha, A, Suthiphosuwan, S et al.. A real-world demonstration of machine learning generalizability in the detection of intracranial hemorrhage on head computerized tomography. Sci Rep. 2021;11 (1):17051. doi: 10.1038/s41598-021-95533-2. PubMed PMID:34426587 PubMed Central PMC8382750.
  6. Colak, E, Kitamura, FC, Hobbs, SB, Wu, CC, Lungren, MP, Prevedello, LM et al.. The RSNA Pulmonary Embolism CT Dataset. Radiol Artif Intell. 2021;3 (2):e200254. doi: 10.1148/ryai.2021200254. PubMed PMID:33937862 PubMed Central PMC8043364.
  7. Merali, ZA, Colak, E, Wilson, JR. Applications of Machine Learning to Imaging of Spinal Disorders: Current Status and Future Directions. Global Spine J. 2021;11 (1_suppl):23S-29S. doi: 10.1177/2192568220961353. PubMed PMID:33890805 PubMed Central PMC8076811.
  8. Gaube, S, Suresh, H, Raue, M, Merritt, A, Berkowitz, SJ, Lermer, E et al.. Do as AI say: susceptibility in deployment of clinical decision-aids. NPJ Digit Med. 2021;4 (1):31. doi: 10.1038/s41746-021-00385-9. PubMed PMID:33608629 PubMed Central PMC7896064.
  9. Lee, EH, Zheng, J, Colak, E, Mohammadzadeh, M, Houshmand, G, Bevins, N et al.. Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT. NPJ Digit Med. 2021;4 (1):11. doi: 10.1038/s41746-020-00369-1. PubMed PMID:33514852 PubMed Central PMC7846563.
  10. Colak, E, Moreland, R, Ghassemi, M. Five principles for the intelligent use of AI in medical imaging. Intensive Care Med. 2021;47 (2):154-156. doi: 10.1007/s00134-020-06316-8. PubMed PMID:33449134 .
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Affiliations & Other Activities

  • Staff Radiologist, Department of Medical Imaging, St. Michael’s Hospital
  • Assistant Professor, Department of Medical Imaging, University of Toronto