Computational Pathology

#WIE #artificial-intelligence #decision-making #deep-learning #learning #histopathology #genomics #machine-learning #pathology #precision-medicine #biomedical #engineering
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Here’s a polished talk description suitable for a symposium program or poster:

Talk Description: Computational Pathology Using AI

This talk will explore the rapidly evolving field of computational pathology and the transformative role of artificial intelligence in advancing precision medicine. By leveraging deep learning and machine learning techniques, computational pathology enables the extraction of high-dimensional, quantitative features from digital histopathology images that are often imperceptible to the human eye.

The presentation will highlight recent advances in integrating pathology with multimodal data sources, including genomics and clinical information, to improve disease characterization, risk stratification, and outcome prediction. Key topics will include algorithm development, model interpretability, and challenges related to data variability, standardization, and clinical deployment.

Through selected case studies, the talk will demonstrate how AI-driven approaches are reshaping diagnostic workflows, enhancing reproducibility, and paving the way toward more personalized and data-driven clinical decision-making.


  Date and Time

  Location

  Hosts

  Registration


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  • 766 Irving Ave
  • Syracuse, New York
  • United States 13210
  • Building: Weiskotten Hall
  • Room Number: 2231
  • Contact Event Hosts

  • SUNY Upstate Medical University & Intelligent Health Computing Core, https://ihcx.org/

  • Co-sponsored by SUNY Upstate Medical University & Intelligent Health Computing Core

  Speakers

Lee Cooper of Northwestern University

Topic:

Prof. Lee A Cooper

Biography:

 

 

Bio
Dr. Cooper received his PhD in Electrical and Computer Engineering from Ohio State University in 2009. He joined the Biomedical Informatics faculty at Emory University in 2012 where he was jointly appointed with Biomedical Engineering at Georgia Institute of Technology. He joined the department of pathology at Northwestern in 2019 as an Associate Professor and Director of Computational Pathology.

Academic Focus
Dr. Cooper leads a research lab focused on advancing machine learning methods for cancer research and fundamental AI innovation. Their work centers on developing algorithms to predict clinical outcomes using multimodal data, including genomics, medical imaging, and digital pathology. The lab also creates tools to extract quantitative phenotypic insights from complex biomedical datasets, enabling more effective data-driven discovery.With a strong emphasis on translational impact, their research aims to improve clinical decision-making and empower investigators with scalable computational tools. Their work has been supported by major funding agencies, including the National Library of Medicine (NLM), National Cancer Institute (NCI), National Institute of Biomedical Imaging and Bioengineering (NIBIB), and National Institute of Neurological Disorders and Stroke (NINDS), as well as industry and foundation partners.

Keywords: Big Data, Bioinformatics, Computational Biology, Genomics, Pathology, Radiology, X-ray, CAT Scan, Medical Imaging