JL Connolly

1.3k total citations · 1 hit paper
8 papers, 1.0k citations indexed

About

JL Connolly is a scholar working on Cancer Research, Oncology and Surgery. According to data from OpenAlex, JL Connolly has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cancer Research, 3 papers in Oncology and 1 paper in Surgery. Recurrent topics in JL Connolly's work include Breast Cancer Treatment Studies (6 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and BRCA gene mutations in cancer (1 paper). JL Connolly is often cited by papers focused on Breast Cancer Treatment Studies (6 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and BRCA gene mutations in cancer (1 paper). JL Connolly collaborates with scholars based in United States, Israel and Canada. JL Connolly's co-authors include Simpson Jf, AD Thor, Clark Gm, Donald L. Weaver, Allen S. Lichter, Patrick L. Fitzgibbons, F P O’Malley, LA Greene, Gary L. Bratthauer and Stephanie J. London and has published in prestigious journals such as The Journal of Cell Biology, Cancer Research and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

JL Connolly

8 papers receiving 995 citations

Hit Papers

align trajectories

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.

Prognostic factors in breast cancer. College of American Pathologists Consensus Statement 1999.

2000 808 citations Patrick L. Fitzgibbons, Donald L. Weaver et al. Archives of Pathology & Laboratory Medicine profile →

Peers

JL Connolly

CR

ONCOL

MB

PFM

RNMI

Anita Bane Canada

Leonard Da Silva Australia

Ian A.J. Lorimer Canada

F. Charbonnier France

Feng‐Yan Li China

P.M. Wencyk United Kingdom

Sasagu Kurozumi Japan

Wolfram Mueller Germany

Kandavel Shanmugam United States

Frank Feleppa Australia

Anita Bane Canada

JL Connolly

509 ×0.9

CR

543 ×1.1

ONCOL

440 ×1.3

MB

288 ×1.0

PFM

55 ×0.4

RNMI

Citations per year, relative to JL Connolly JL Connolly (= 1×) peers Anita Bane

Countries citing papers authored by JL Connolly

Since Specialization

Citations

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

Fields of papers citing papers by JL Connolly

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of JL Connolly

This figure shows the co-authorship network connecting the top 25 collaborators of JL Connolly. A scholar is included among the top collaborators of JL Connolly 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 JL Connolly. JL Connolly 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.

Dawood, Shaheenah, et al.. (2009). Defining breast cancer prognosis based on molecular phenotypes: results from a large cohort study.. Cancer Research. 69(2_Supplement). 1068–1068. 2 indexed citations

2.

Recht, Abram, et al.. (2006). Local recurrence after conservative surgery and radiation therapy for ductal carcinoma in situ: Possible importance of family history.. PubMed. 1(1). 55–61. 24 indexed citations

3.

Fitzgibbons, Patrick L., Donald L. Weaver, AD Thor, et al.. (2000). Prognostic factors in breast cancer. College of American Pathologists Consensus Statement 1999.. Archives of Pathology & Laboratory Medicine. 124(7). 966–78. 808 indexed citations breakdown →

4.

Connolly, JL, et al.. (1998). The relationship between lymphatic vessel invasion, tumor size and pathologic nodal status: Can we predict who can avoid a third field in the absence of axillary dissection. International Journal of Radiation Oncology*Biology*Physics. 42(1). 251–251. 1 indexed citations

5.

Connolly, JL, et al.. (1998). Factors associated with regional nodal failure in patients with early stage breast cancer with 0–3 positive axillary nodes following tangential irradiation alone. International Journal of Radiation Oncology*Biology*Physics. 42(1). 181–181. 6 indexed citations

6.

Connolly, JL, et al.. (1996). Comparative expression of the LINE-1 p40 protein in human breast carcinomas and normal breast tissues.. PubMed. 8(6). 239–47. 57 indexed citations

7.

London, Stephanie J., et al.. (1992). A prospective study of benign breast disease and the risk of breast cancer. International Journal of Gynecology & Obstetrics. 39(2). 159–160. 10 indexed citations

8.

Connolly, JL, et al.. (1979). Rapid, sequential changes in surface morphology of PC12 pheochromocytoma cells in response to nerve growth factor. The Journal of Cell Biology. 82(3). 820–827. 133 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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