OV SCOUT

OVarian Cancer Subtype Classification and Outlier DeTection

Project aim

Epithelial ovarian cancers have five major histotypes. We are launching an AI competition to build classifiers to accurately identify these major histotypes as well as the rare subtypes of ovarian cancers. This is a collaborative work with the Ovarian Tumor Tissue Analysis (OTTA) consortium.

Meeting - May 31, 2022

Watch the recording from the meeting.

Download the slides from the meeting.

Resources discussed in 5/31 meeting:

  • Multi-Reader ROC studies with Split-Plot Designs: A Comparison of Statistical Methods (link)

  • Impact of prevalence and case distribution in lab-based diagnostic imaging studies (link)

  • Agreement in Histological Assessment of Mitotic Activity Between Microscopy and Digital Whole Slide Images Informs Conversion for Clinical Diagnosis (link)

Project leaders

 

Ali Bashashati

Dr. Bashashati is currently the director of artificial intelligence (AI) research in the Ovarian Cancer Research Program (OVCARE) at BC Cancer as well as a faculty member in the Department of Pathology & Laboratory Medicine and the School of Biomedical Engineering (SBME) at the University of British Columbia.

Dr. Bashashati’s research area lies at the interface between computational, engineering and biomedical sciences. He is interested in developing machine learning algorithms to combine various sources of 'omics and imaging data (including digitized pathology slides) in the context of cancer. Dr. Bashashati runs BC’s Translational Digital Pathology AI program and works closely with clinicians and biologists across various health sites. Through AI, they intend to improve pathology efficiency, identify new biomarkers for treatment selection and derive biological insights that can be studied in various disease models in the lab.

Hossein Farahani

Lead Machine Learning Scientist

  • PhD in Computer Science, KTH Royal Institute of Technology

  • MSc in Space Science & Technology, The Julius Maximilians University of Würzburg, Germany

  • MSc in Robotics & Automation Engineering, Gwangju Institute of Science and Technology, South Korea

  • BSc in Mechanical Engineering, Sharif University of Technology, Iran

Maryam Asadi

Post-doctoral Fellow

  • PhD in Computer Engineering (Artificial Intelligence), Sharif University of Technology, Iran

  • MSc in Software Engineering, IUST, Iran

  • BSc in Software Engineering, IUST, Iran

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