Jonathan M. M. Hall

1.7k total citations · 1 hit paper
37 papers, 1.0k citations indexed

About

Jonathan M. M. Hall is a scholar working on Nuclear and High Energy Physics, Atomic and Molecular Physics, and Optics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Jonathan M. M. Hall has authored 37 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Nuclear and High Energy Physics, 8 papers in Atomic and Molecular Physics, and Optics and 7 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Jonathan M. M. Hall's work include Quantum Chromodynamics and Particle Interactions (15 papers), Particle physics theoretical and experimental studies (12 papers) and High-Energy Particle Collisions Research (11 papers). Jonathan M. M. Hall is often cited by papers focused on Quantum Chromodynamics and Particle Interactions (15 papers), Particle physics theoretical and experimental studies (12 papers) and High-Energy Particle Collisions Research (11 papers). Jonathan M. M. Hall collaborates with scholars based in Australia, United States and China. Jonathan M. M. Hall's co-authors include Derek B. Leinweber, R. D. Young, A. W. Thomas, Matthew VerMilyea, Sonya M. Diakiw, Michelle Perugini, Don Perugini, Nicolas Riesen, Tanya M. Monro and Tess Reynolds and has published in prestigious journals such as Physical Review Letters, Scientific Reports and Physics Letters B.

In The Last Decade

Jonathan M. M. Hall

36 papers receiving 971 citations

Hit Papers

Development of an artificial intelligence-based assessmen... 2020 2026 2022 2024 2020 50 100 150

Peers

Jonathan M. M. Hall
Christopher A Mancuso United States
Sean M. Robinson United States
D. P. Fussell Australia
Piotr M. Starewicz United States
Robert J. Doll Netherlands
Peter G. Morris United Kingdom
Brian J. Coffey United States
Laura M. Schultz United States
Christopher A Mancuso United States
Jonathan M. M. Hall
Citations per year, relative to Jonathan M. M. Hall Jonathan M. M. Hall (= 1×) peers Christopher A Mancuso

Countries citing papers authored by Jonathan M. M. Hall

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan M. M. Hall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan M. M. 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 Jonathan M. M. Hall. The network helps show where Jonathan M. M. Hall may publish in the future.

Co-authorship network of co-authors of Jonathan M. M. Hall

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan M. M. Hall. A scholar is included among the top collaborators of Jonathan M. M. 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 Jonathan M. M. Hall. Jonathan M. M. 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.
Hall, Jonathan M. M., Trung Van Nguyen, Don Perugini, et al.. (2024). Use of federated learning to develop an artificial intelligence model predicting usable blastocyst formation from pre-ICSI oocyte images. Reproductive BioMedicine Online. 49(6). 104403–104403. 2 indexed citations
2.
Diakiw, Sonya M., et al.. (2023). Efficient automated error detection in medical data using deep-learning and label-clustering. Scientific Reports. 13(1). 19587–19587. 3 indexed citations
3.
Diakiw, Sonya M., Jonathan M. M. Hall, Matthew VerMilyea, et al.. (2022). An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos. Reproductive BioMedicine Online. 45(6). 1105–1117. 39 indexed citations
4.
Dakka, M. Abou, Sonya M. Diakiw, Matthew VerMilyea, et al.. (2022). A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data. Scientific Reports. 12(1). 8888–8888. 40 indexed citations
5.
Hall, Jonathan M. M.. (2021). Reclaiming the Past. Cornell University Press eBooks. 1 indexed citations
6.
Diakiw, Sonya M., Matthew VerMilyea, Jonathan M. M. Hall, et al.. (2021). O-222 An artificial intelligence model that was trained on pregnancy outcomes for embryo viability assessment is highly correlated with Gardner Score. Human Reproduction. 36(Supplement_1). 1 indexed citations
7.
Dakka, M. Abou, Jonathan M. M. Hall, Sonya M. Diakiw, et al.. (2021). Automated detection of poor-quality data: case studies in healthcare. Scientific Reports. 11(1). 18005–18005. 16 indexed citations
8.
Dakka, M. Abou, Matthew VerMilyea, Don Perugini, et al.. (2020). IDENTIFYING INHERENT POOR QUALITY EMBRYO DATA USING ARTIFICIAL INTELLIGENCE TO IMPROVE AI PERFORMANCE AND CLINICAL REPORTING. Fertility and Sterility. 114(3). e148–e148. 1 indexed citations
9.
VerMilyea, Matthew, Jonathan M. M. Hall, Don Perugini, et al.. (2019). Artificial intelligence: non-invasive detection of morphological features associated with abnormalities in chromosomes 21 and 16. Fertility and Sterility. 112(3). e237–e238. 2 indexed citations
10.
Liu, Zhan-Wei, Jonathan M. M. Hall, Derek B. Leinweber, A. W. Thomas, & Jia-Jun Wu. (2017). Structure of the Λ(1405) from Hamiltonian effective field theory. Physical review. D. 95(1). 42 indexed citations
11.
Hall, Jonathan M. M., Tess Reynolds, Matthew R. Henderson, et al.. (2017). Unified theory of whispering gallery multilayer microspheres with single dipole or active layer sources. Optics Express. 25(6). 6192–6192. 13 indexed citations
12.
Hall, Jonathan M. M., F. Alexandre, Shahraam Afshar V., et al.. (2016). Determining the geometric parameters of microbubble resonators from their spectra. Journal of the Optical Society of America B. 34(1). 44–44. 3 indexed citations
13.
Hall, Jonathan M. M., Waseem Kamleh, Derek B. Leinweber, et al.. (2015). Lattice QCD Evidence that theΛ(1405)Resonance is an Antikaon-Nucleon Molecule. Physical Review Letters. 114(13). 132002–132002. 116 indexed citations
14.
Leinweber, Derek B., Waseem Kamleh, Jonathan M. M. Hall, et al.. (2015). On the Structure of the Lambda 1405. 94–94. 3 indexed citations
15.
Hall, Jonathan M. M.. (2013). Artifact and Artifice. 1 indexed citations
16.
Hall, Jonathan M. M., Derek B. Leinweber, B. J. Owen, & R. D. Young. (2013). Finite-volume corrections to charge radii. Physics Letters B. 725(1-3). 101–105. 9 indexed citations
17.
Hall, Jonathan M. M., Derek B. Leinweber, & R. D. Young. (2013). Chiral extrapolations for nucleon electric charge radii. Physical review. D. Particles, fields, gravitation, and cosmology. 88(1). 21 indexed citations
18.
Hall, Jonathan M. M., Derek B. Leinweber, & R. D. Young. (2012). Chiral extrapolations for nucleon magnetic moments. Physical review. D. Particles, fields, gravitation, and cosmology. 85(9). 21 indexed citations
19.
Hall, Jonathan M. M.. (2004). Scattering from inhomogeneous material cylinders using a modified fast far field approximation. 3. 520–523. 1 indexed citations
20.
Carpenter, Linda L., Zeljko Jocic, Jonathan M. M. Hall, S. Rasmussen, & Lawrence H. Price. (1999). Mirtazapine Augmentation in the Treatment of Refractory Depression. The Journal of Clinical Psychiatry. 60(1). 45–49. 96 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.

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