Lawrence Hall

48.6k total citations · 5 hit papers
283 papers, 31.2k citations indexed

About

Lawrence Hall is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Lawrence Hall has authored 283 papers receiving a total of 31.2k indexed citations (citations by other indexed papers that have themselves been cited), including 168 papers in Artificial Intelligence, 86 papers in Computer Vision and Pattern Recognition and 60 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Lawrence Hall's work include Radiomics and Machine Learning in Medical Imaging (53 papers), Medical Image Segmentation Techniques (45 papers) and AI in cancer detection (39 papers). Lawrence Hall is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (53 papers), Medical Image Segmentation Techniques (45 papers) and AI in cancer detection (39 papers). Lawrence Hall collaborates with scholars based in United States, China and Saudi Arabia. Lawrence Hall's co-authors include Kevin W. Bowyer, W. Philip Kegelmeyer, Nitesh V. Chawla, Dmitry B. Goldgof, James C. Bezdek, Laurence P. Clarke, Robert J. Gillies, Robert P. Velthuizen, Robert A. Gatenby and A. Bensaid and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Signal Processing.

In The Last Decade

Lawrence Hall

270 papers receiving 29.9k citations

Hit Papers

SMOTE: Synthetic Minority Over-sampling Technique 1993 2026 2004 2015 2002 2012 1993 1995 2012 5.0k 10.0k 15.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. SMOTE: Synthetic Minority Over-sampling Technique
    2002 19.7k citations Nitesh V. Chawla, Kevin W. Bowyer et al. profile →
  2. Radiomics: the process and the challenges
    2012 1.7k citations Matthew B. Schabath, Dmitry B. Goldgof et al. profile →
  3. Review of MR image segmentation techniques using pattern recognition
    1993 687 citations Lawrence Hall et al. profile →
  4. MRI segmentation: Methods and applications
    1995 514 citations Lawrence Hall et al. profile →
  5. Fuzzy c-Means Algorithms for Very Large Data
    2012 353 citations Lawrence Hall et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lawrence Hall United States 48 14.6k 5.8k 5.7k 2.9k 2.1k 283 31.2k
Greg S. Corrado United States 34 16.3k 1.1× 4.7k 0.8× 5.6k 1.0× 3.8k 1.3× 1.1k 0.5× 57 28.1k
Yudong Zhang China 88 8.8k 0.6× 5.9k 1.0× 8.2k 1.4× 776 0.3× 1.0k 0.5× 1.0k 29.4k
Kevin W. Bowyer United States 61 12.9k 0.9× 2.0k 0.4× 13.1k 2.3× 4.5k 1.5× 742 0.3× 385 36.0k
Taghi M. Khoshgoftaar United States 65 16.4k 1.1× 2.9k 0.5× 5.9k 1.0× 10.9k 3.7× 619 0.3× 654 38.9k
Nitesh V. Chawla United States 55 18.1k 1.2× 1.7k 0.3× 3.0k 0.5× 4.8k 1.6× 708 0.3× 320 33.5k
Corinna Cortes United States 33 20.7k 1.4× 2.5k 0.4× 13.5k 2.4× 3.5k 1.2× 870 0.4× 76 58.8k
W. Philip Kegelmeyer United States 15 11.5k 0.8× 1.6k 0.3× 2.3k 0.4× 2.6k 0.9× 666 0.3× 38 21.7k
Aaron Courville Canada 39 15.3k 1.0× 2.8k 0.5× 15.3k 2.7× 1.3k 0.5× 405 0.2× 103 36.5k
Huiling Chen China 97 20.0k 1.4× 2.6k 0.4× 5.3k 0.9× 1.4k 0.5× 584 0.3× 822 40.8k

Countries citing papers authored by Lawrence Hall

Since Specialization
Citations

This map shows the geographic impact of Lawrence Hall's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lawrence Hall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence Hall more than expected).

Fields of papers citing papers by Lawrence Hall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lawrence Hall. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lawrence Hall. The network helps show where Lawrence Hall may publish in the future.

Co-authorship network of co-authors of Lawrence Hall

This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence Hall. A scholar is included among the top collaborators of Lawrence Hall based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lawrence Hall. Lawrence Hall is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Weinheimer, Carla J., et al.. (2024). Synergizing Deep Learning-Enabled Preprocessing and Human–AI Integration for Efficient Automatic Ground Truth Generation. Bioengineering. 11(5). 434–434. 1 indexed citations
2.
3.
Hall, Lawrence, et al.. (2024). Repeatability of Fine-Tuning Large Language Models Illustrated Using QLoRA. IEEE Access. 12. 153221–153231. 5 indexed citations
4.
Goldgof, Dmitry B., Lawrence Hall, Joseph Johnson, et al.. (2023). Classifying Malignancy in Prostate Glandular Structures from Biopsy Scans with Deep Learning. Cancers. 15(8). 2335–2335. 2 indexed citations
5.
Goldgof, Dmitry B., et al.. (2022). A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 7458–7477. 6 indexed citations
6.
Hall, Lawrence, et al.. (2022). Achieving Multisite Generalization for CNN-Based Disease Diagnosis Models by Mitigating Shortcut Learning. IEEE Access. 10. 78726–78738. 7 indexed citations
7.
Chiu, George T.‐C., Dawn Melley, Kathleen Kramer, et al.. (2021). IEEE/ASME Transactions on Mechatronics. IEEE/ASME Transactions on Mechatronics. 26(6). C2–C2. 6 indexed citations
8.
Goldgof, Dmitry B., et al.. (2021). An adaptive digital stain separation method for deep learning-based automatic cell profile counts. Journal of Neuroscience Methods. 354. 109102–109102. 5 indexed citations
9.
Goldgof, Dmitry B., et al.. (2020). Challenges for the Repeatability of Deep Learning Models. IEEE Access. 8. 211860–211868. 51 indexed citations
10.
Cherezov, Dmitry, Dmitry B. Goldgof, Lawrence Hall, et al.. (2019). Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness. Scientific Reports. 9(1). 4500–4500. 34 indexed citations
11.
Phoulady, Hady Ahmady, Dmitry B. Goldgof, Lawrence Hall, Kevin Nash, & Peter R. Mouton. (2019). Automatic stereology of mean nuclear size of neurons using an active contour framework. Journal of Chemical Neuroanatomy. 96. 110–115. 3 indexed citations
12.
Zhou, Mu, Jacob G. Scott, Baishali Chaudhury, et al.. (2017). Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches. American Journal of Neuroradiology. 39(2). 208–216. 272 indexed citations
13.
Hall, Lawrence, et al.. (2016). Spectral sparsification in spectral clustering. 2301–2306. 10 indexed citations
14.
Banfield, Robert E., et al.. (2008). Semi-supervised learning on large complex simulations. Proceedings - International Conference on Pattern Recognition. 1–4. 9 indexed citations
15.
Hall, Lawrence, Richard Collins, Kevin W. Bowyer, & Robert E. Banfield. (2003). Error-based pruning of decision trees grown on very large data sets can work!. 233–238. 7 indexed citations
16.
Chawla, Nitesh V., Thomas E. Moore, Kevin W. Bowyer, et al.. (2001). Bagging-like effects for decision trees and neural nets in protein secondary structure prediction. 50–59. 5 indexed citations
17.
Levinson, Robert, Susan L. Epstein, Loren Terveen, et al.. (1994). AAAI 1993 Fall Symposium Reports. AI Magazine. 15(1). 14. 2 indexed citations
18.
Hall, Lawrence. (1993). Some Comments on and an Extension to Activity Structures for Intelligent Systems. Journal of Korean institute of intelligent systems. 3(1). 23–28.
19.
Hall, Lawrence, et al.. (1992). The validation of fuzzy knowledge-based systems. John Wiley & Sons, Inc. eBooks. 589–604. 13 indexed citations
20.
Hall, Lawrence & Wyllis Bandler. (1985). Relational Knowledge Acquisition.. 509–513. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Greg S. Corrado Breakdown of academic impact, for papers by Yudong Zhang Breakdown of academic impact, for papers by Kevin W. Bowyer Breakdown of academic impact, for papers by Taghi M. Khoshgoftaar Breakdown of academic impact, for papers by Nitesh V. Chawla Breakdown of academic impact, for papers by Corinna Cortes Breakdown of academic impact, for papers by W. Philip Kegelmeyer Breakdown of academic impact, for papers by Aaron Courville Breakdown of academic impact, for papers by Huiling Chen
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2026