Artificial Intelligence in Healthcare

AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone

Academic Edition, Chapter 29 - References/Further Reading

General Edition, Chapter 12 - References/Further Reading


  1. Wilson ML, Fleming KA, Kuti MA, Looi LM, Lago N, Ru K. Access to pathology and laboratory medicine services: a crucial gap. The Lancet. 2018 May 12;391(10133):1927-38.
  2. Size EH. Share Trends Analysis Report by Product. By Application, By Region, And Segment Forecasts. 2020;2027.
  3. Browning L, Colling R, Rakha E, Rajpoot N, Rittscher J, James JA, Salto-Tellez M, Snead DR, Verrill C. Digital pathology and artificial intelligence will be key to supporting clinical and academic cellular pathology through COVID-19 and future crises: the PathLAKE Consortium perspective. Journal of clinical pathology. 2020 Jul 3.
  4. Tomczak K, Czerwińska P, Wiznerowicz M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemporary oncology. 2015;19(1A):A68.
  5. Crawford D. Joint Pathology Center selects Huron Digital Pathology’s image search engine — OBIO - Ontario Bioscience Innovation Organization [Internet]. OBIO - Ontario Bioscience Innovation Organization; 2020 [cited 2021 Jan 22]. Available from:
  6. Parwani AV. Next generation diagnostic pathology: use of digital pathology and artificial intelligence tools to augment a pathological diagnosis.
  7. Lagotto - Huron Digital Pathology [Internet]. [cited 2021 Jan 22]. Available from:
  8. Steiner DF, MacDonald R, Liu Y, Truszkowski P, Hipp JD, Gammage C, Thng F, Peng L, Stumpe MC. Impact of deep learning assistance on the histopathologic review of lymph nodes for metastatic breast cancer. The American journal of surgical pathology. 2018 Dec;42(12):1636.
  9. Chen PH, Gadepalli K, MacDonald R, Liu Y, Nagpal K, Kohlberger T, Dean J, Corrado GS, Hipp JD, Stumpe MC. Microscope 2.0: an augmented reality microscope with real-time artificial intelligence integration. arXiv preprint arXiv:1812.00825. 2018 Nov 21.
  10. Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A. Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology. Nature reviews Clinical oncology. 2019 Nov;16(11):703-15.
  11. Parwani AV. Next generation diagnostic pathology: use of digital pathology and artificial intelligence tools to augment a pathological diagnosis.
  12. Nagpal K, Foote D, Liu Y, Chen PH, Wulczyn E, Tan F, Olson N, Smith JL, Mohtashamian A, Wren JH, Corrado GS. Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer. NPJ digital medicine. 2019 Jun 7;2(1):1-0.
  13. Ibrahim A, Gamble P, Jaroensri R, Abdelsamea MM, Mermel CH, Chen PH, Rakha EA. Artificial intelligence in digital breast pathology: Techniques and applications. The Breast. 2020 Feb 1;49:267-73.
  14. Shamai G, Binenbaum Y, Slossberg R, Duek I, Gil Z, Kimmel R. Artificial intelligence algorithms to assess hormonal status from tissue microarrays in patients with breast cancer. JAMA network open. 2019 Jul 3;2(7):e197700-.
  15. Martin DR, Hanson JA, Gullapalli RR, Schultz FA, Sethi A, Clark DP. A deep learning convolutional neural network can recognize common patterns of injury in gastric pathology. Archives of pathology & laboratory medicine. 2020 Mar;144(3):370-8.
  16. Halo Ai [Internet]. 2019 [cited 2021 Feb 19]. Available from:
  17. Indica labs, octo launch global COVID-19 digital pathology repository [Internet]. 2020 [cited 2021 Feb 19]. Available from: