Basic/Clinical Science Session
Applications of Artificial Intelligence to Medical Kidney Biopsy Interpretation
November 03, 2022 | 02:00 PM - 04:00 PM
Location: W315, Orange County Convention Center, West Building
Session Description
Although the kidney biopsy remains an essential diagnostic and prognostic tool, considerable interobserver variability is an important limitation in assessing key elements of the biopsy, such as cellular injury, fibrosis, and inflammation in the glomerular, tubulointerstitial, and vascular compartments. This session discusses the increasing interest in use of image analysis and machine learning to promote uniformity of kidney biopsy interpretation and the development of algorithms for assessing prognosis and guiding therapy.
Learning Objective(s)
- Describe the fundamentals and advantages of using machine learning in the analysis of kidney biopsies and the current application of this technology in research and clinical practice
- Define the role of digital pathology and computer-aided analysis of these images in clinical trials of glomerular diseases and establishing taxonomies of glomerular diseases, particularly podocytopathies
- Discuss how the use of deep learning-based analysis can improve on current morphology-based analysis of kidney transplant biopsies and provide new tools for assessing prognosis and guiding therapy
Learning Pathway(s)
- Pathology
Moderators
- Laura Barisoni, MD
- Avi Z. Rosenberg, MD, PhD
Presentations
- Image Analysis in the Quantitation of Interstitial Fibrosis and Glomerulosclerosis
02:00 PM - 02:30 PM
Alton Brad Farris, MD, MBA
- Computational Segmentation and Quantification in Diabetic Nephropathy
02:30 PM - 03:00 PM
Pinaki Sarder, PhD
- Deep Learning Classification of Kidney Transplant Pathology
03:00 PM - 03:30 PM
Peter Boor, MD, PhD
- High-Throughput Quality Control, Annotation, and Labeling in Kidney Digital Pathology Repositories for Biomarker Discovery
03:30 PM - 04:00 PM
Andrew Janowczyk, PhD
