Related references
Note: Only part of the references are listed.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
Lisa Browning et al.
JOURNAL OF CLINICAL PATHOLOGY (2021)
Artificial Intelligence and the Medical Physicist: Welcome to the Machine
Michele Avanzo et al.
APPLIED SCIENCES-BASEL (2021)
Artificial intelligence and digital pathology: Opportunities and implications for immuno-oncology
Faranak Sobhani et al.
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER (2021)
A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score
Geza Halasz et al.
JOURNAL OF MEDICAL INTERNET RESEARCH (2021)
Special Issue on Digital Pathology, Tissue Image Analysis, Artificial Intelligence, and Machine Learning: Approximation of the Effect of Novel Technologies on Toxicologic Pathology
Famke Aeffner et al.
TOXICOLOGIC PATHOLOGY (2021)
Building a central repository landmarks a new era for artificial intelligence-assisted digital pathology development in Europe
Leena Latonen et al.
EUROPEAN JOURNAL OF CANCER (2021)
Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology
Oliver C. Turner et al.
TOXICOLOGIC PATHOLOGY (2020)
Banff Digital Pathology Working Group: Going digital in transplant pathology
Alton B. Farris et al.
AMERICAN JOURNAL OF TRANSPLANTATION (2020)
Convergence of Digital Pathology and Artificial Intelligence Tools in Anatomic Pathology Practice: Current Landscape and Future Directions
Anil V. Parwani et al.
ADVANCES IN ANATOMIC PATHOLOGY (2020)
Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology
Kaustav Bera et al.
JCO CLINICAL CANCER INFORMATICS (2020)
Multiresolution Application of Artificial Intelligence in Digital Pathology for Prediction of Positive Lymph Nodes From Primary Tumors in Bladder Cancer
Stephanie A. Harmon et al.
JCO CLINICAL CANCER INFORMATICS (2020)
Predicting Cardiovascular Risk in Athletes: Resampling Improves Classification Performance
Davide Barbieri et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)
A narrative review of digital pathology and artificial intelligence: focusing on lung cancer
Taro Sakamoto et al.
TRANSLATIONAL LUNG CANCER RESEARCH (2020)
Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice
Richard Colling et al.
JOURNAL OF PATHOLOGY (2019)
Digital pathology and artificial intelligence
Muhammad Khalid Khan Niazi et al.
LANCET ONCOLOGY (2019)
Artificial intelligence in digital pathology - new tools for diagnosis and precision oncology
Kaustav Bera et al.
NATURE REVIEWS CLINICAL ONCOLOGY (2019)
Next generation diagnostic pathology: use of digital pathology and artificial intelligence tools to augment a pathological diagnosis
Anil V. Parwani
DIAGNOSTIC PATHOLOGY (2019)
Physician perspectives on integration of artificial intelligence into diagnostic pathology
Shihab Sarwar et al.
NPJ DIGITAL MEDICINE (2019)
Integration of Tablet Technologies in the e-Laboratory of Cytology: A Health Technology Assessment
Daniele Giansanti et al.
TELEMEDICINE AND E-HEALTH (2014)
Expanding application of digital pathology in Japan - from education, telepathology to autodiagnosis
Yasunari Tsuchihashi
DIAGNOSTIC PATHOLOGY (2011)
The design of a health technology assessment system in telepathology
Daniele Giansanti et al.
TELEMEDICINE JOURNAL AND E-HEALTH (2008)
Share Paper
