J. Helgeson

441 total citations
8 papers, 313 citations indexed

About

J. Helgeson is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Cancer Research. According to data from OpenAlex, J. Helgeson has authored 8 papers receiving a total of 313 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Health Informatics and 2 papers in Cancer Research. Recurrent topics in J. Helgeson's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Cancer Genomics and Diagnostics (2 papers). J. Helgeson is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Cancer Genomics and Diagnostics (2 papers). J. Helgeson collaborates with scholars based in United States. J. Helgeson's co-authors include Víctor G. Dávila‐Román, Jack H. Ladenson, A S Jaffe, Robert C. Hickner, George M. Lawson, Ron McCullough, Daniel S. Grosu, Juan‐Sebastian Saldivar, Eyad Almasri and Daniel H. Farkas and has published in prestigious journals such as Journal of Clinical Oncology, Annals of Oncology and Metabolism.

In The Last Decade

J. Helgeson

8 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Helgeson United States	7	101	98	91	63	59	8	313
Weiqi Wang United States	9	25 0.2×	4 0.0×	39 0.4×	31 0.5×	14 0.2×	13	310
Edson Santos Ferreira‐Filho Brazil	11	18 0.2×	98 1.0×	24 0.3×	43 0.7×	10 0.2×	29	416
Doaa Amin Ireland	6	18 0.2×	15 0.2×	20 0.2×	19 0.3×	20 0.3×	18	365
Elisa Salvi Italy	8	17 0.2×	8 0.1×	6 0.1×	38 0.6×	10 0.2×	26	280
Maria Carmina Pau Italy	12	31 0.3×	24 0.2×	133 1.5×	37 0.6×	12 0.2×	21	366
Hafsa Majid Pakistan	7	3 0.0×	28 0.3×	41 0.5×	22 0.3×	34 0.6×	55	255
Xinhao Cheng China	5	71 0.7×	21 0.2×	19 0.2×	10 0.2×	146 2.5×	11	233
Paraskevi Christofidou United Kingdom	9	5 0.0×	19 0.2×	40 0.4×	24 0.4×	86 1.5×	12	300
Sean J. Delaney United States	9	13 0.1×	19 0.2×	51 0.6×	19 0.3×	48 0.8×	24	241
Michel Makhlouf United States	12	3 0.0×	129 1.3×	18 0.2×	53 0.8×	8 0.1×	27	323

Countries citing papers authored by J. Helgeson

Since Specialization

Citations

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

Fields of papers citing papers by J. Helgeson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Helgeson. 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 J. Helgeson. The network helps show where J. Helgeson may publish in the future.

Co-authorship network of co-authors of J. Helgeson

This figure shows the co-authorship network connecting the top 25 collaborators of J. Helgeson. A scholar is included among the top collaborators of J. Helgeson 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 J. Helgeson. J. Helgeson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Haddad, Tufia C., J. Helgeson, Anita M. Preininger, et al.. (2021). Accuracy of an Artificial Intelligence System for Cancer Clinical Trial Eligibility Screening: Retrospective Pilot Study. JMIR Medical Informatics. 9(3). e27767–e27767. 39 indexed citations

2.

Leventakos, Konstantinos, J. Helgeson, Aaron S. Mansfield, et al.. (2019). P1.16-14 Effects of an Artificial Intelligence (AI) System on Clinical Trial Enrollment in Lung Cancer. Journal of Thoracic Oncology. 14(10). S592–S592. 6 indexed citations

3.

Jin, Zhao-Hui, Tufia C. Haddad, Joleen M. Hubbard, et al.. (2019). A pilot study to implement an artificial intelligence (AI) system for gastrointestinal cancer clinical trial matching. Annals of Oncology. 30. v582–v582. 4 indexed citations

4.

Leventakos, Konstantinos, J. Helgeson, Aaron S. Mansfield, et al.. (2019). Implementation of artificial intelligence (AI) for lung cancer clinical trial matching in a tertiary cancer center. Annals of Oncology. 30. ii74–ii74. 7 indexed citations

5.

Helgeson, J., Melissa Rammage, Alexandra Urman, et al.. (2018). Clinical performance pilot using cognitive computing for clinical trial matching at Mayo Clinic.. Journal of Clinical Oncology. 36(15_suppl). e18598–e18598. 16 indexed citations

6.

Haddad, Tufia C., et al.. (2018). Impact of a cognitive computing clinical trial matching system in an ambulatory oncology practice.. Journal of Clinical Oncology. 36(15_suppl). 6550–6550. 19 indexed citations

7.

Helgeson, J., Theresa Boomer, Eyad Almasri, et al.. (2015). Clinical outcome of subchromosomal events detected by whole‐genome noninvasive prenatal testing. Prenatal Diagnosis. 35(10). 999–1004. 102 indexed citations

8.

Lawson, George M., J. Helgeson, Víctor G. Dávila‐Román, et al.. (1997). Prolonged exercise decreases serum leptin concentrations. Metabolism. 46(10). 1109–1112. 120 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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