Thomas S. Winokur

University of Alabama at Birmingham

Papers

1

Total Citations

4

H-Index

1

About

Thomas S. Winokur is a researcher whose work lies at the intersection of pathology and computational imaging, with a particular focus on telepathology and automated tissue analysis. His most cited contribution, "An Automated Tissue Preclassification Approach for Telepathology: Implementation and Performance Analysis" (2004, 4 citations), addresses a critical bottleneck in remote diagnostic workflows: the need for efficient, pre-screening methods to classify tissue samples before human review. By developing an automated preclassification system, Winokur aimed to reduce the cognitive load on pathologists and improve diagnostic throughput in telepathology settings—a field that relies on telecommunications to transmit biopsy images for remote interpretation. While his citation count is modest, his work reflects an early and targeted effort to integrate machine-driven analysis into clinical pathology, anticipating later advances in digital pathology and AI-assisted diagnostics. Winokur’s research contributes to the foundational challenge of making telepathology more practical and scalable, highlighting his role in shaping the tools that enable pathologists to render accurate diagnoses from afar.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
An Automated Tissue Preclassification Approach for Telepathology: Implementation and Performance Analysis
4 citations · 2004
📈 Most Prolific Year: 2004 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Alabama at Birmingham

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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