Laurie J. Mango

1.1k total citations
25 papers, 776 citations indexed

About

Laurie J. Mango is a scholar working on Epidemiology, Artificial Intelligence and Oncology. According to data from OpenAlex, Laurie J. Mango has authored 25 papers receiving a total of 776 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Epidemiology, 10 papers in Artificial Intelligence and 3 papers in Oncology. Recurrent topics in Laurie J. Mango's work include Cervical Cancer and HPV Research (13 papers), AI in cancer detection (10 papers) and Global Cancer Incidence and Screening (3 papers). Laurie J. Mango is often cited by papers focused on Cervical Cancer and HPV Research (13 papers), AI in cancer detection (10 papers) and Global Cancer Incidence and Screening (3 papers). Laurie J. Mango collaborates with scholars based in United States, France and Costa Rica. Laurie J. Mango's co-authors include Martha L. Hutchinson, Mitchell Greenberg, Concepción Bratti, Leopold G. Koss, Jorge Morales, Paul Elgert, Ileana Balmaceda, Mark E. Sherman, Klaus Schréiber and Rolando Herrero and has published in prestigious journals such as Cancer, American Journal of Obstetrics and Gynecology and Cancer Letters.

In The Last Decade

Laurie J. Mango

24 papers receiving 736 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Laurie J. Mango United States	14	535	277	158	127	94	25	776
Jasenka Matisic Canada	17	493 0.9×	97 0.4×	187 1.2×	169 1.3×	122 1.3×	30	782
E Gradwell United Kingdom	7	298 0.6×	101 0.4×	83 0.5×	121 1.0×	52 0.6×	10	479
George L. Wied United States	20	379 0.7×	127 0.5×	230 1.5×	243 1.9×	196 2.1×	77	1.3k
John Panayiotides Greece	14	229 0.4×	106 0.4×	112 0.7×	128 1.0×	60 0.6×	28	509
Dirk van Niekerk Canada	18	722 1.3×	92 0.3×	318 2.0×	305 2.4×	176 1.9×	50	987
J Summerell United Kingdom	9	277 0.5×	89 0.3×	62 0.4×	129 1.0×	70 0.7×	18	519
Roy Zhang United States	14	680 1.3×	101 0.4×	225 1.4×	327 2.6×	245 2.6×	30	1.0k
D. Eakins United Kingdom	5	267 0.5×	89 0.3×	59 0.4×	132 1.0×	41 0.4×	8	438
Maria Demarco United States	14	606 1.1×	227 0.8×	289 1.8×	175 1.4×	75 0.8×	20	844
Jean Mather United Kingdom	8	612 1.1×	63 0.2×	185 1.2×	276 2.2×	98 1.0×	10	694

Countries citing papers authored by Laurie J. Mango

Since Specialization

Citations

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

Fields of papers citing papers by Laurie J. Mango

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laurie J. Mango

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Bergeron, Christine, et al.. (2000). Quality Control of Cervical Cytology in High-Risk Women. Acta Cytologica. 44(2). 151–157. 17 indexed citations

2.

Herrero, Rolando, Concepción Bratti, Mitchell Greenberg, et al.. (1999). Cervicography screening for cervical cancer among 8460 women in a high-risk population. American Journal of Obstetrics and Gynecology. 180(2). 290–298. 50 indexed citations

3.

Herrero, Rolando, Mitchell Greenberg, A. Hildesheim, et al.. (1999). Cervicography Screening for Cervical Cancer Among 8,460 Women in a High-Risk Population. Journal of Lower Genital Tract Disease. 3(4). 273–273. 2 indexed citations

4.

Takahashi, Masayoshi, G Brugal, H. Christen, et al.. (1998). Digital Imagery/Telecytology. Acta Cytologica. 42(1). 148–164. 38 indexed citations

5.

Vooijs, Peter, et al.. (1998). Computerized Training and Proficiency Testing. Acta Cytologica. 42(1). 141–147. 18 indexed citations

6.

Sherman, Mark E., Mark Schiffman, Rolando Herrero, et al.. (1998). Performance of a semiautomated papanicolaou smear screening system. Cancer. 84(5). 273–280. 39 indexed citations

7.

Mango, Laurie J. & Philip T. Valente. (1998). Neural Network–Assisted Analysis and Microscopic Rescreening in Presumed Negative Cervical Cytologic Smears. Acta Cytologica. 42(1). 227–232. 17 indexed citations

8.

Niekerk, W.A. Van, Charles J. Dunton, Ralph M. Richart, et al.. (1998). Colposcopy, Cervicography, Speculoscopy and Endoscopy. Acta Cytologica. 42(1). 33–49. 17 indexed citations

9.

Radensky, Paul W. & Laurie J. Mango. (1998). Interactive Neural Network–Assisted Screening. Acta Cytologica. 42(1). 246–252. 11 indexed citations

10.

Mango, Laurie J. & Paul W. Radensky. (1998). Interactive Neural Network–Assisted Screening. Acta Cytologica. 42(1). 233–245. 10 indexed citations

11.

Mango, Laurie J. & Paul W. Radensky. (1998). Neural network-assisted (“NNA”) analysis of cervical smears: pooled effectiveness results and economic analysis. Primary Care Update for OB/GYNS. 5(4). 162–163. 4 indexed citations

12.

Sherman, Mark E., Mark H. Schiffman, Attila T. Lörincz, et al.. (1997). Cervical specimens collected in liquid buffer are suitable for both cytologic screening and ancillary human papillomavirus testing. Cancer. 81(2). 89–97. 11 indexed citations

13.

Herrero, Rolando, Mark H. Schiffman, Concepción Bratti, et al.. (1997). Design and methods of a population-based natural history study of cervical neoplasia in a rural province of Costa Rica: the Guanacaste Project. Revista Panamericana de Salud Pública. 1(5). 362–375. 178 indexed citations

14.

Sherman, Mark E., Mark H. Schiffman, Attila T. Lörincz, et al.. (1997). Cervical specimens collected in liquid buffer are suitable for both cytologic screening and ancillary human papillomavirus testing. Cancer. 81(2). 89–97. 95 indexed citations

15.

Mango, Laurie J.. (1997). Clinical Validation of Interactive Cytologic Screening. Acta Cytologica. 41(1). 93–97. 12 indexed citations

16.

Sherman, Mark E., Mark Schiffman, Laurie J. Mango, et al.. (1997). Evaluation of PAPNET testing as an ancillary tool to clarify the status of the "atypical" cervical smear.. PubMed. 10(6). 564–71. 14 indexed citations

17.

Mango, Laurie J.. (1996). Reducing false negatives in clinical practice: The role of neural network technology. American Journal of Obstetrics and Gynecology. 175(4). 1114–1119. 18 indexed citations

18.

Mango, Laurie J.. (1996). Neuromedical Systems, Inc.. Acta Cytologica. 40(1). 53–59. 12 indexed citations

19.

Koss, Leopold G., et al.. (1994). Evaluation of the PAPNET^™Cytologic Screening System for Quality Control of Cervical Smears. American Journal of Clinical Pathology. 101(2). 220–229. 93 indexed citations

20.

Mango, Laurie J.. (1994). Computer-assisted cervical cancer screening using neural networks. Cancer Letters. 77(2-3). 155–162. 79 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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