P H Bartels

868 total citations
40 papers, 613 citations indexed

About

P H Bartels is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, P H Bartels has authored 40 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 9 papers in Pulmonary and Respiratory Medicine and 7 papers in Molecular Biology. Recurrent topics in P H Bartels's work include AI in cancer detection (14 papers), Prostate Cancer Treatment and Research (6 papers) and Prostate Cancer Diagnosis and Treatment (5 papers). P H Bartels is often cited by papers focused on AI in cancer detection (14 papers), Prostate Cancer Treatment and Research (6 papers) and Prostate Cancer Diagnosis and Treatment (5 papers). P H Bartels collaborates with scholars based in United States, Italy and United Kingdom. P H Bartels's co-authors include Rodolfo Montironi, D Thompson, Peter W. Hamilton, George L. Wied, L G Koss, Marluce Bibbo, Neil Anderson, Roberta Mazzucchelli, Anna R. Graham and James R. Marshall and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Nutrition and European Urology.

In The Last Decade

P H Bartels

40 papers receiving 588 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
P H Bartels United States	16	177	153	145	109	98	40	613
J Holmquist Sweden	10	145 0.8×	83 0.5×	160 1.1×	189 1.7×	56 0.6×	17	569
Bill A. Rampy United States	11	84 0.5×	100 0.7×	259 1.8×	174 1.6×	60 0.6×	18	685
Nazeel Ahmad United States	9	178 1.0×	142 0.9×	313 2.2×	411 3.8×	177 1.8×	21	915
B. Nordin Sweden	10	88 0.5×	59 0.4×	227 1.6×	128 1.2×	58 0.6×	20	508
Shohreh Dickinson United States	12	151 0.9×	112 0.7×	143 1.0×	110 1.0×	30 0.3×	25	527
Jun Xiang China	18	183 1.0×	100 0.7×	244 1.7×	154 1.4×	59 0.6×	50	1.0k
Juan Zhou China	16	98 0.6×	112 0.7×	168 1.2×	153 1.4×	48 0.5×	39	684
Chee Leong Cheng Singapore	16	65 0.4×	126 0.8×	230 1.6×	193 1.8×	105 1.1×	36	1.0k
Ryan Deaton United States	17	44 0.2×	176 1.2×	260 1.8×	91 0.8×	61 0.6×	39	737
Sighild Westman‐Naeser Sweden	9	107 0.6×	28 0.2×	117 0.8×	106 1.0×	89 0.9×	15	420

Countries citing papers authored by P H Bartels

Since Specialization

Citations

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

Fields of papers citing papers by P H Bartels

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P H Bartels. 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 P H Bartels. The network helps show where P H Bartels may publish in the future.

Co-authorship network of co-authors of P H Bartels

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

All Works

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20 of 20 papers shown

Scarpelli, Marina, Rodolfo Montironi, Peter W. Hamilton, et al.. (2004). Karyometry detects subvisual differences in chromatin organisation state between non-recurrent and recurrent papillary urothelial neoplasms of low malignant potential. Journal of Clinical Pathology. 57(11). 1201–1207. 9 indexed citations

McCluggage, W. Glenn, Gareth J. Price, James J. Diamond, et al.. (2002). Expert system support using a Bayesian belief network for the classification of endometrial hyperplasia. The Journal of Pathology. 197(3). 403–414. 19 indexed citations

Mariuzzi, Laura, et al.. (2001). Early stromal invasion in cervical cancer: immunocytochemical changes occurring in infiltrating neoplastic cells.. PubMed. 5(4). 133–8. 1 indexed citations

Adlercreutz, Herman, Witold Mazur, P H Bartels, et al.. (2000). Phytoestrogens and Prostate Disease. Journal of Nutrition. 130(3). 658S–659S. 84 indexed citations

Montironi, Rodolfo, Roberta Mazzucchelli, James R. Marshall, & P H Bartels. (1999). Prostate cancer prevention: review of target populations, pathological biomarkers, and chemopreventive agents.. Journal of Clinical Pathology. 52(11). 793–803. 28 indexed citations

Bartels, P H, et al.. (1998). Nuclear chromatin texture in prostatic lesions. II. PIN and malignancy associated changes.. PubMed. 20(5). 397–406. 34 indexed citations

Bartels, P H, et al.. (1998). Machine vision in the detection of prostate lesions in histologic sections.. PubMed. 20(5). 358–64. 6 indexed citations

Bartels, P H, David R. Thompson, Rodolfo Montironi, G.M. Mariuzzi, & Peter W. Hamilton. (1996). Automated Reasoning System inHistopathologic Diagnosis andPrognosis of Prostate Cancer andIts Precursors. European Urology. 30(2). 222–233. 9 indexed citations

Montironi, Rodolfo, et al.. (1996). Androgen-Deprived ProstateAdenocarcinoma: Evaluation ofTreatment-Related Changes versusNo Distinctive Treatment Effectwith a Bayesian Belief Network. European Urology. 30(3). 307–315. 20 indexed citations

10.

Montironi, Rodolfo, W F Whimster, Yrjö Collan, et al.. (1996). How to develop and use a Bayesian Belief Network.. Journal of Clinical Pathology. 49(3). 194–201. 18 indexed citations

11.

Bartels, P H, et al.. (1996). Analysis of the CapillaryArchitecture in the Precursors ofProstate Cancer: Recent Findingsand New Concepts. European Urology. 30(2). 191–200. 44 indexed citations

12.

Thompson, Deborah J., et al.. (1996). Knowledge-guided histometry of the basal cell layer in prostatic intraepithelial neoplasia.. PubMed. 18(2). 177–84. 2 indexed citations

13.

Elledge, Richard, Gary M. Clark, Myo Thant, et al.. (1995). Rapid in vitro assay for predicting response to fluorouracil in patients with metastatic breast cancer.. Journal of Clinical Oncology. 13(2). 419–423. 8 indexed citations

14.

Bartels, P H, et al.. (1992). Construction of the knowledge file for an image understanding system. Pathology - Research and Practice. 188(4-5). 396–404. 5 indexed citations

15.

Minimo, Corrado, et al.. (1991). Value of the cribriformity factor in grading prostatic carcinoma.. PubMed. 13(6). 411–7. 1 indexed citations

16.

Bibbo, Marluce, Carla Di Loreto, Harvey E. Dytch, et al.. (1990). Tissue architectural features for the grading of prostatic carcinoma.. PubMed. 12(4). 229–36. 9 indexed citations

17.

Bartels, P H. (1989). The diagnostic pattern in histopathology.. PubMed. 91(4 Suppl 1). S7–13. 8 indexed citations

18.

Graham, Anna R., et al.. (1988). Micromorphometry of colonic lesions.. PubMed. 59(3). 397–402. 15 indexed citations

19.

Galera-Davidson, H, Marluce Bibbo, P H Bartels, et al.. (1986). Differential diagnosis between follicular adenoma and follicular carcinoma of the thyroid by marker features.. PubMed. 8(3). 195–200. 15 indexed citations

20.

Sherman, Andrew B., L G Koss, Karen Schreiber, et al.. (1981). Bladder cancer diagnosis by image analysis of cells in voided urine using a small computer.. PubMed. 3(3). 239–49. 11 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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