M. I. Ross

2.2k total citations
17 papers, 1.6k citations indexed

About

M. I. Ross is a scholar working on Oncology, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, M. I. Ross has authored 17 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Oncology, 4 papers in Molecular Biology and 4 papers in Artificial Intelligence. Recurrent topics in M. I. Ross's work include Cutaneous Melanoma Detection and Management (12 papers), CAR-T cell therapy research (4 papers) and AI in cancer detection (4 papers). M. I. Ross is often cited by papers focused on Cutaneous Melanoma Detection and Management (12 papers), CAR-T cell therapy research (4 papers) and AI in cancer detection (4 papers). M. I. Ross collaborates with scholars based in United States, Brazil and Australia. M. I. Ross's co-authors include Jeffrey E. Gershenwald, Martín C. Mihm, William R. Jewell, Walley Temple, Raymond L. Barnhill, Marshall M. Urist, Charles M. Balch, Alfred A. Bartolucci, Harold J. Wanebo and Thomas J. Smith and has published in prestigious journals such as Journal of Clinical Oncology, JNCI Journal of the National Cancer Institute and Annals of Surgery.

In The Last Decade

M. I. Ross

17 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. I. Ross United States 10 1.4k 522 461 259 240 17 1.6k
Christopher A. Puleo United States 13 1.3k 0.9× 617 1.2× 325 0.7× 180 0.7× 236 1.0× 17 1.6k
Frank Glass United States 15 1.7k 1.2× 799 1.5× 376 0.8× 252 1.0× 404 1.7× 36 2.1k
Duan‐Ren Wen United States 18 1.2k 0.9× 419 0.8× 415 0.9× 491 1.9× 179 0.7× 29 1.7k
Andrea Maurichi Italy 24 1.3k 0.9× 385 0.7× 378 0.8× 477 1.8× 251 1.0× 65 1.6k
David P. Rapaport United States 15 926 0.7× 475 0.9× 234 0.5× 205 0.8× 233 1.0× 27 1.4k
Hans Starz Germany 18 980 0.7× 553 1.1× 195 0.4× 154 0.6× 263 1.1× 37 1.2k
Marjorie H. Colman Australia 15 1.2k 0.8× 248 0.5× 592 1.3× 152 0.6× 125 0.5× 18 1.4k
Jonathan R. Stretch Australia 31 2.3k 1.7× 887 1.7× 862 1.9× 380 1.5× 438 1.8× 121 2.9k
Kerwin F. Shannon Australia 32 2.6k 1.8× 1.0k 2.0× 957 2.1× 393 1.5× 424 1.8× 130 3.5k
Peter J. Bostick United States 18 1.1k 0.8× 374 0.7× 368 0.8× 228 0.9× 131 0.5× 20 1.7k

Countries citing papers authored by M. I. Ross

Since Specialization
Citations

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

Fields of papers citing papers by M. I. Ross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. I. Ross

This figure shows the co-authorship network connecting the top 25 collaborators of M. I. Ross. A scholar is included among the top collaborators of M. I. Ross 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 M. I. Ross. M. I. Ross 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.
Chesney, Jason, Frances A. Collichio, Robert Hans Ingemar Andtbacka, et al.. (2016). Interim safety and efficacy of a randomized (1:1), open-label phase 2 study of talimogene laherparepvec (T) and ipilimumab (I) vs I alone in unresected, stage IIIB-IV melanoma. Annals of Oncology. 27. vi380–vi380. 13 indexed citations
2.
Saïag, Philippe, Ralf Gutzmer, P.A. Ascierto, et al.. (2016). Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT). Annals of Oncology. 27(10). 1947–1947. 20 indexed citations
3.
Andtbacka, Robert Hans Ingemar, Howard L. Kaufman, Frances A. Collichio, et al.. (2015). 3334 Durable complete responses (CR) in patients (pts) with stage IIIB-IV melanoma treated with talimogene laherparepvec (T-VEC) in OPTiM. European Journal of Cancer. 51. S676–S676. 2 indexed citations
4.
Agarwala, Sanjiv S., John F. Thompson, B. Mark Smithers, et al.. (2013). Locoregional disease control in metastatic melanoma: Exploratory analysis from phase 2 testing of intralesional rose bengal. European Journal of Cancer. 49. 3 indexed citations
5.
Xing, Yan, Yulia Bronstein, M. I. Ross, et al.. (2010). Contemporary Diagnostic Imaging Modalities for the Staging and Surveillance of Melanoma Patients: a Meta-analysis. JNCI Journal of the National Cancer Institute. 103(2). 129–142. 220 indexed citations
6.
Thompson, John F., B. Mark Smithers, M. I. Ross, et al.. (2010). Chemoablation of metastatic melanoma with rose bengal (PV-10).. Journal of Clinical Oncology. 28(15_suppl). 8534–8534. 6 indexed citations
7.
Xing, Yan, Yulia Bronstein, M. I. Ross, et al.. (2010). Diagnostic imaging modalities for the surveillance of melanoma patients: A meta-analysis.. Journal of Clinical Oncology. 28(15_suppl). 8581–8581. 4 indexed citations
8.
Fournier, Keith F., Yan Xing, M. I. Ross, et al.. (2008). Survival in patients with synchronous versus metachronous lymph node (LN) involvement in stage III melanoma: Is there a difference?. Journal of Clinical Oncology. 26(15_suppl). 9034–9034. 1 indexed citations
9.
Balch, Charles M., Seng-Jaw Soong, Michael B. Atkins, et al.. (2004). An Evidence-based Staging System for Cutaneous Melanoma. CA A Cancer Journal for Clinicians. 54(3). 131–149. 303 indexed citations
10.
Soong, Seng‐Jaw, M. I. Ross, Marshall M. Urist, et al.. (2000). Long-Term Results of a Multi-Institutional Randomized Trial Comparing Prognostic Factors and Surgical Results for Intermediate Thickness Melanomas (1.0 to 4.0 mm). Annals of Surgical Oncology. 7(2). 87–97. 340 indexed citations
11.
Mirza, Nadeem Q., Georges Vlastos, Funda Meric, et al.. (2000). Ductal Carcinoma-In-Situ: Long-Term Results of Breast-Conserving Therapy. Annals of Surgical Oncology. 7(9). 656–664. 30 indexed citations
12.
Gershenwald, Jeffrey E., Antônio C. Buzaid, & M. I. Ross. (1998). CLASSIFICATION AND STAGING OF MELANOMA. Hematology/Oncology Clinics of North America. 12(4). 737–765. 27 indexed citations
13.
Gershenwald, Jeffrey E., Paul F. Mansfield, Jeffrey E. Lee, et al.. (1998). Improved sentinel lymph node localization in patients with primary melanoma with the use of radiolabeled colloid. Surgery. 124(2). 203–210. 160 indexed citations
14.
Ross, M. I.. (1997). Prospective randomized trials in melanoma: Defining contemporary surgical roles. Cancer treatment and research. 90. 1–27. 4 indexed citations
15.
Balch, Charles M., Seng-Jaw Soong, Alfred A. Bartolucci, et al.. (1996). Efficacy of an Elective Regional Lymph Node Dissection of 1 to 4 mm Thick Melanomas for Patients 60 Years of Age and Younger. Annals of Surgery. 224(3). 255–266. 461 indexed citations
16.
Ross, M. I.. (1996). STAGING EVALUATION AND SURVEILLANCE FOR MELANOMA PATIENTS IN A FISCALLY RESTRICTIVE MEDICAL ENVIRONMENT. Surgical Clinics of North America. 76(6). 1423–1432. 10 indexed citations
17.
Heaton, Keith M., et al.. (1993). Prognostic implications of DNA index in patients with stage III cutaneous melanoma. The American Journal of Surgery. 166(6). 648–653. 7 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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