David P. Ng

868 total citations
25 papers, 582 citations indexed

About

David P. Ng is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Physiology. According to data from OpenAlex, David P. Ng has authored 25 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Pathology and Forensic Medicine and 6 papers in Physiology. Recurrent topics in David P. Ng's work include Lymphoma Diagnosis and Treatment (7 papers), Single-cell and spatial transcriptomics (6 papers) and Chronic Lymphocytic Leukemia Research (4 papers). David P. Ng is often cited by papers focused on Lymphoma Diagnosis and Treatment (7 papers), Single-cell and spatial transcriptomics (6 papers) and Chronic Lymphocytic Leukemia Research (4 papers). David P. Ng collaborates with scholars based in United States, Canada and Germany. David P. Ng's co-authors include John P. Pribble, Charles J. Fisher, Michael A. Catalano, Steven M. Opal, Gus J. Slotman, George Emmanuel, Duane C. Bloedow, Roger C. Bone, Mark A Cervinski and Jorge Luis Valdés González and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

David P. Ng

20 papers receiving 573 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David P. Ng United States 9 222 179 131 84 84 25 582
Olivier Collignon Luxembourg 13 115 0.5× 31 0.2× 177 1.4× 23 0.3× 52 0.6× 22 747
Zeyu Xiong United States 18 73 0.3× 267 1.5× 256 2.0× 133 1.6× 45 0.5× 34 786
Gwen Clarke Canada 14 96 0.4× 63 0.4× 39 0.3× 173 2.1× 79 0.9× 67 1.2k
S. J. Machin United Kingdom 12 58 0.3× 44 0.2× 46 0.4× 218 2.6× 120 1.4× 22 857
Eloísa Urrechaga Spain 21 135 0.6× 44 0.2× 31 0.2× 176 2.1× 54 0.6× 69 1.0k
Timothy J. Fischer United States 8 94 0.4× 34 0.2× 110 0.8× 46 0.5× 132 1.6× 11 513
Hada C. Macher Spain 13 152 0.7× 55 0.3× 133 1.0× 53 0.6× 91 1.1× 31 567
Ian Longair United Kingdom 10 66 0.3× 367 2.1× 18 0.1× 194 2.3× 46 0.5× 12 790
Larry D. Roi United States 11 77 0.3× 65 0.4× 62 0.5× 134 1.6× 48 0.6× 25 741
Charalampos Chrelias Greece 17 143 0.6× 109 0.6× 69 0.5× 25 0.3× 69 0.8× 61 836

Countries citing papers authored by David P. Ng

Since Specialization
Citations

This map shows the geographic impact of David P. Ng'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 David P. Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David P. Ng more than expected).

Fields of papers citing papers by David P. Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David P. Ng. 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 David P. Ng. The network helps show where David P. Ng may publish in the future.

Co-authorship network of co-authors of David P. Ng

This figure shows the co-authorship network connecting the top 25 collaborators of David P. Ng. A scholar is included among the top collaborators of David P. Ng 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 David P. Ng. David P. Ng 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.
Spies, Nicholas C., Jyoti Kumar, Oscar Silva, et al.. (2025). The Evolution and Recent Advances in Diagnostic Criteria for Idiopathic Multicentric Castleman Disease. American Journal of Hematology. 100(11). 2064–2073.
2.
Spies, Nicholas C., et al.. (2025). Machine Learning Methods in Clinical Flow Cytometry. Cancers. 17(3). 483–483. 4 indexed citations
3.
Spies, Nicholas C. & David P. Ng. (2025). Performance metrics for machine learning solutions in laboratory medicine. Laboratory Medicine. 56(6). 597–607.
4.
Mathison, Blaine A., Ryan C. Shean, Brendan O’Fallon, et al.. (2025). Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens. Microbiology Spectrum. 13(8). e0060225–e0060225.
5.
Durtschi, Jacob, et al.. (2025). Clinical validation of a real‐time machine learning‐based system for the detection of acute myeloid leukemia by flow cytometry. Cytometry Part B Clinical Cytometry. 108(5). 392–403.
6.
Agarwal, Archana M., et al.. (2024). Applications of Flow Cytometry in Diagnosis and Evaluation of Red Blood Cell Disorders. Clinics in Laboratory Medicine. 44(3). 495–509. 1 indexed citations
7.
Dinalankara, Wikum, David P. Ng, Luigi Marchionni, & Paul D. Simonson. (2024). Comparison of three machine learning algorithms for classification of B‐cell neoplasms using clinical flow cytometry data. Cytometry Part B Clinical Cytometry. 106(4). 282–293. 4 indexed citations
8.
Ng, David P., Paul D. Simonson, Attila Tárnok, et al.. (2024). Recommendations for using artificial intelligence in clinical flow cytometry. Cytometry Part B Clinical Cytometry. 106(4). 228–238. 10 indexed citations
9.
Ravkov, Eugene V., et al.. (2024). Converting an HLA‐B27 flow assay from the BD FACSCanto to the BD FACSLyric. Cytometry Part B Clinical Cytometry. 108(1). 67–76. 1 indexed citations
10.
Mause, Erica R. Vander, Jillian M. Baker, Sabarinath Venniyil Radhakrishnan, et al.. (2023). Systematic single amino acid affinity tuning of CD229 CAR T cells retains efficacy against multiple myeloma and eliminates on-target off-tumor toxicity. Science Translational Medicine. 15(705). eadd7900–eadd7900. 17 indexed citations
11.
Lu, Kevin, Joshua Menke, David P. Ng, et al.. (2022). Cytomorphologic features of pediatric-type follicular lymphoma on fine needle aspiration biopsy: case series and a review of the literature. Journal of the American Society of Cytopathology. 11(5). 281–294. 1 indexed citations
12.
13.
Ng, David P.. (2021). Flow cytometric myeloma measurable residual disease testing in the era of targeted therapies. International Journal of Laboratory Hematology. 43(S1). 71–77. 2 indexed citations
14.
Ng, David P., et al.. (2021). Pax-5 negative B-cell Lymphoma. SHILAP Revista de lepidopterología. 25. 200474–200474.
15.
Yeung, Cecilia C.S., et al.. (2017). Impact of copy neutral loss of heterozygosity and total genome aberrations on survival in myelodysplastic syndrome. Modern Pathology. 31(4). 569–580. 11 indexed citations
16.
Ng, David P., David Wu, Brent L. Wood, & Jonathan R. Fromm. (2015). Computer-Aided Detection of Rare Tumor Populations in Flow Cytometry. American Journal of Clinical Pathology. 144(3). 517–524. 12 indexed citations
17.
Ng, David P. & Brent L. Wood. (2014). Unsupervised Discovery of Early Markers of Erythroid Maturation in Human Donor Marrow. Blood. 124(21). 4304–4304. 1 indexed citations
18.
Suriawinata, Arief A., et al.. (2013). Short-term preoperative diet modification reduces steatosis and blood loss in patients undergoing liver resection. Surgery. 154(5). 1031–1037. 33 indexed citations
19.
20.
Fisher, Charles J., Gus J. Slotman, Steven M. Opal, et al.. (1994). Initial evaluation of human recombinant interleukin-1 receptor antagonist in the treatment of sepsis syndrome: A randomized, open-label, placebocontrolled multicenter trial. Critical Care Medicine. 22(1). 12–21. 351 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 Olivier Collignon Breakdown of academic impact, for papers by Zeyu Xiong Breakdown of academic impact, for papers by Gwen Clarke Breakdown of academic impact, for papers by S. J. Machin Breakdown of academic impact, for papers by Eloísa Urrechaga Breakdown of academic impact, for papers by Timothy J. Fischer Breakdown of academic impact, for papers by Hada C. Macher Breakdown of academic impact, for papers by Ian Longair Breakdown of academic impact, for papers by Larry D. Roi Breakdown of academic impact, for papers by Charalampos Chrelias
Rankless by CCL
2026