Ran Godrich

824 total citations
5 papers, 180 citations indexed

About

Ran Godrich is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ran Godrich has authored 5 papers receiving a total of 180 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ran Godrich's work include Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Prostate Cancer Diagnosis and Treatment (3 papers). Ran Godrich is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Prostate Cancer Diagnosis and Treatment (3 papers). Ran Godrich collaborates with scholars based in United States and United Kingdom. Ran Godrich's co-authors include Jillian Sue, Victor E. Reuter, Christopher Kanan, Patricia Raciti, David S. Klimstra, Jeremy D. Kunz, Thomas J. Fuchs, Leo Grady, George R. DeMuth and Julian Viret and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Modern Pathology.

In The Last Decade

Ran Godrich

4 papers receiving 179 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ran Godrich United States	3	132	103	67	38	26	5	180
Jeremy D. Kunz United States	3	132 1.0×	103 1.0×	67 1.0×	38 1.0×	25 1.0×	4	179
Richard W. Lee United Kingdom	4	89 0.7×	125 1.2×	50 0.7×	60 1.6×	25 1.0×	6	240
Manuela Vecsler United States	4	196 1.5×	179 1.7×	63 0.9×	69 1.8×	45 1.7×	5	290
Yoel Shoshan Israel	4	132 1.0×	120 1.2×	42 0.6×	48 1.3×	21 0.8×	5	177
Kishio Kuroda Japan	8	95 0.7×	118 1.1×	91 1.4×	18 0.5×	18 0.7×	14	218
Mathijn de Jong Netherlands	5	86 0.7×	99 1.0×	82 1.2×	32 0.8×	57 2.2×	7	229
Chi-Cheng Fu China	8	89 0.7×	151 1.5×	122 1.8×	15 0.4×	33 1.3×	12	216
Mi-ri Kwon South Korea	10	136 1.0×	219 2.1×	53 0.8×	33 0.9×	44 1.7×	27	351
Juan Antonio Retámero Spain	8	176 1.3×	116 1.1×	71 1.1×	48 1.3×	82 3.2×	13	299
Jong Seok Ahn South Korea	5	70 0.5×	130 1.3×	46 0.7×	67 1.8×	17 0.7×	9	201

Countries citing papers authored by Ran Godrich

Since Specialization

Citations

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

Fields of papers citing papers by Ran Godrich

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ran Godrich

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

All Works

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5 of 5 papers shown

1.

Raciti, Patricia, Jillian Sue, Juan Antonio Retámero, et al.. (2022). Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection. Archives of Pathology & Laboratory Medicine. 147(10). 1178–1185. 54 indexed citations

2.

Hanna, Matthew G., Patricia Raciti, Alican Bozkurt, et al.. (2022). Abstract PD11-02: Subtyping invasive carcinomas and high-risk lesions for machine learning based breast pathology. Cancer Research. 82(4_Supplement). PD11–2.

3.

Hanna, Matthew G., Patricia Raciti, Ran Godrich, et al.. (2021). Abstract PD6-03: Clinical-grade detection of breast cancer in biopsies and excisions using machine learning. Cancer Research. 81(4_Supplement). PD6–3. 1 indexed citations

4.

Raciti, Patricia, Jillian Sue, Ran Godrich, et al.. (2020). Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies. Modern Pathology. 33(10). 2058–2066. 121 indexed citations

5.

Dogdas, Belma, Christopher Kanan, Patricia Raciti, et al.. (2020). Computational pathological identification of prostate cancer following neoadjuvant treatment.. Journal of Clinical Oncology. 38(15_suppl). e14052–e14052. 4 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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