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Jun Bai

Medical Image Analysis AI-driven Cancer Diagnostics AI Drug Discovery Deep Learning
University of Cincinnati Computer Science

About

Jun Bai is an Assistant Professor at the University of Cincinnati. She earned her Ph.D. in Computer Science and Engineering from the University of Connecticut in 2023. She holds a Master of Science in Computer Science (2019) and a Master of Science in Education in Interdisciplinary Studies (2015), both from the University of Dayton. Her research and practice interests include Machine Learning, Deep Learning, Medical Image Analysis, AI-driven cancer and disease diagnostics, and AI drug discovery.

Research Performance Summary

29
Total Papers
435
Total Citations
8
H-Index
2021-2026
Active Research Span

First Recorded Paper

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review

Year: 2021

Citations: 197

Venue: Medical image analysis 71

Latest Recorded Paper

Continual Learning for Histopathology Image Classification in Class Incremental Learning

Year: 2026

Citations: 0

Venue: Medical Imaging with Deep Learning-Validation Papers

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2026
3
2025
9
2024
4
2023
3
2022
7
2021
3

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 11
Journal 2
Book 0

Top Coauthors

Bai Nabavi Wang

Research Impact by Period

2025-2026

Period Stats
Papers 12
Citations 13
Avg. Citations / Paper 1.1
H-Index 1

2020-2024

Period Stats
Papers 17
Citations 422
Avg. Citations / Paper 24.8
H-Index 7

Contact and Professional Links

Contact Information

baiju@ucmail.uc.edu
5135569789

Detected Research Keywords

Digital Breast Tomosynthesis Breast Cancer Detection Weakly Supervised Learning Supervised Learning Model Learning Model Prostate Model Prostate Cancer Prostate Cancer Diagnosis Cancer Diagnosis Gleason Diagnosis Gleason Grading Gleason Grading Histopathology