Lyssa Friedman

2.3k total citations · 1 hit paper
17 papers, 1.7k citations indexed

About

Lyssa Friedman is a scholar working on Endocrinology, Diabetes and Metabolism, Oncology and Surgery. According to data from OpenAlex, Lyssa Friedman has authored 17 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Endocrinology, Diabetes and Metabolism, 7 papers in Oncology and 4 papers in Surgery. Recurrent topics in Lyssa Friedman's work include Thyroid Cancer Diagnosis and Treatment (9 papers), Neutropenia and Cancer Infections (4 papers) and Erythropoietin and Anemia Treatment (3 papers). Lyssa Friedman is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (9 papers), Neutropenia and Cancer Infections (4 papers) and Erythropoietin and Anemia Treatment (3 papers). Lyssa Friedman collaborates with scholars based in United States, Italy and South Africa. Lyssa Friedman's co-authors include Giulia C. Kennedy, Richard B. Lanman, Virginia A. LiVolsi, Juan Rosaí, Martha A. Zeiger, David L. Steward, James Diggans, Darya Chudova, Jonathan I. Wilde and Richard T. Kloos and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and Blood.

In The Last Decade

Lyssa Friedman

16 papers receiving 1.6k citations

Hit Papers

Preoperative Diagnosis of Benign Thyroid Nodules with Ind... 2012 2026 2016 2021 2012 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lyssa Friedman United States 9 1.5k 755 459 193 147 17 1.7k
Dario Tumino Italy 19 1.6k 1.0× 859 1.1× 276 0.6× 226 1.2× 233 1.6× 41 1.8k
P. Sean Walsh United States 12 963 0.6× 455 0.6× 297 0.6× 151 0.8× 89 0.6× 27 1.2k
Domenico Meringolo Italy 15 1.4k 0.9× 867 1.1× 192 0.4× 144 0.7× 235 1.6× 22 1.5k
Lucia Brilli Italy 14 1.1k 0.7× 492 0.7× 225 0.5× 119 0.6× 171 1.2× 35 1.3k
Kazuhisa Toda Japan 17 1.2k 0.8× 631 0.8× 200 0.4× 103 0.5× 114 0.8× 34 1.3k
Nikola Bešič Slovenia 22 720 0.5× 585 0.8× 221 0.5× 158 0.8× 129 0.9× 82 1.3k
Kyung Won Kim South Korea 13 819 0.5× 336 0.4× 143 0.3× 159 0.8× 96 0.7× 19 912
Laura Moss United Kingdom 9 987 0.6× 609 0.8× 133 0.3× 95 0.5× 143 1.0× 16 1.2k
Mary B. Casey United States 13 568 0.4× 360 0.5× 133 0.3× 146 0.8× 138 0.9× 20 983
Michael Tuttle United States 13 760 0.5× 365 0.5× 167 0.4× 71 0.4× 68 0.5× 24 836

Countries citing papers authored by Lyssa Friedman

Since Specialization
Citations

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

Fields of papers citing papers by Lyssa Friedman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lyssa Friedman

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

All Works

17 of 17 papers shown
1.
Kloos, Richard T., Jessica Reynolds, P. Sean Walsh, et al.. (2013). Does Addition ofBRAFV600E Mutation Testing Modify Sensitivity or Specificity of the Afirma Gene Expression Classifier in Cytologically Indeterminate Thyroid Nodules?. The Journal of Clinical Endocrinology & Metabolism. 98(4). E761–E768. 51 indexed citations
2.
Cibas, Edmund S., Zubair Baloch, Giovanni Fellegara, et al.. (2013). A Prospective Assessment Defining the Limitations of Thyroid Nodule Pathologic Evaluation. Annals of Internal Medicine. 159(5). 325–332. 151 indexed citations
3.
Hershman, Jerome M., Giovanni Fellegara, LiVolsi Va, et al.. (2013). Cytopathologic Diagnosis of Thyroid Nodules Varies Considerably.
5.
Alexander, Erik K., Giulia C. Kennedy, Zubair Baloch, et al.. (2012). Preoperative Diagnosis of Benign Thyroid Nodules with Indeterminate Cytology. New England Journal of Medicine. 367(8). 705–715. 791 indexed citations breakdown →
6.
Duick, Daniel S., Joshua Klopper, James Diggans, et al.. (2012). The Impact of Benign Gene Expression Classifier Test Results on the Endocrinologist-Patient Decision to Operate on Patients with Thyroid Nodules with Indeterminate FNA Cytopathology. Thyroid. 1099874924–1099874924. 1 indexed citations
7.
Walsh, P. Sean, Jonathan I. Wilde, Edward Tom, et al.. (2012). Analytical Performance Verification of a Molecular Diagnostic for Cytology-Indeterminate Thyroid Nodules. The Journal of Clinical Endocrinology & Metabolism. 97(12). E2297–E2306. 45 indexed citations
8.
Friedman, Lyssa, Giulia C. Kennedy, Hui Wang, et al.. (2010). A Large Multicenter Correlation Study of Thyroid Nodule Cytopathology and Histopathology. Thyroid. 21(3). 243–251. 274 indexed citations
9.
Chudova, Darya, Jonathan I. Wilde, Eric T. Wang, et al.. (2010). Molecular Classification of Thyroid Nodules Using High-Dimensionality Genomic Data. The Journal of Clinical Endocrinology & Metabolism. 95(12). 5296–5304. 192 indexed citations
10.
Friedman, Lyssa, et al.. (2009). The EDUCATE Study: A Continuing Education Exemplar for Clinical Practice Guideline Implementation. Clinical journal of oncology nursing. 13(2). 219–230. 16 indexed citations
11.
Naeim, Arash, Lyssa Friedman, David J. Pasta, et al.. (2009). Patterns of Care in Community-Based Oncology Practices for Anemia Associated With Myelosuppressive Chemotherapy. Journal of Oncology Practice. 5(5). 236–243. 1 indexed citations
12.
Naeim, Arash, Lyssa Friedman, David J. Pasta, et al.. (2007). Prophylaxis of chemotherapy-induced neutropenia: Patterns of care in U.S. community oncology practices. Journal of Clinical Oncology. 25(18_suppl). 9123–9123. 4 indexed citations
13.
Friedman, Lyssa, Arash Naeim, David J. Pasta, et al.. (2007). Adherence to anemia treatment guidelines in U.S. community oncology practices. Journal of Clinical Oncology. 25(18_suppl). 19525–19525. 1 indexed citations
14.
Naeim, Arash, Lyssa Friedman, Eric P. Elkin, et al.. (2007). Patterns of Care in Patients with Chemotherapy Receiving Erythropoiesis Stimulating Agents (ESAs).. Blood. 110(11). 964–964. 1 indexed citations
15.
Kramer, Rita, et al.. (2005). Chemotherapy-induced amenorrhea is increased in patients treated with adjuvant doxorubicin and cyclophosphamide (AC) followed by a taxane (T). Journal of Clinical Oncology. 23(16_suppl). 651–651. 10 indexed citations
16.
George, Stephanie M., John Crowley, S S Ellenberg, et al.. (1993). Discussion: Stephen George, a survey of monitoring practices in cancer clinical trials: Stephanie Green and John Crowley, data monitoring committees for Southwest Oncology Group clinical trials. Statistics in Medicine. 12. 457–459. 2 indexed citations
17.
Singer, Jack W., et al.. (1983). The effect of blood cooling prior to granulocyte collection. Transfusion. 23(4). 342–343. 2 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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