Trissia Brown

540 total citations
5 papers, 220 citations indexed

About

Trissia Brown is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oncology. According to data from OpenAlex, Trissia Brown has authored 5 papers receiving a total of 220 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Artificial Intelligence and 2 papers in Oncology. Recurrent topics in Trissia Brown's work include Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (3 papers) and Colorectal Cancer Screening and Detection (2 papers). Trissia Brown is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (3 papers) and Colorectal Cancer Screening and Detection (2 papers). Trissia Brown collaborates with scholars based in United States, Austria and United Kingdom. Trissia Brown's co-authors include Po-Hsuan Cameron Chen, Craig H. Mermel, Yun Liu, Melissa Moran, Timo Kohlberger, Martin C. Stumpe, Jason Hipp, David F. Steiner, Fraser Elisabeth Tan and Lily H. Peng and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Trissia Brown

5 papers receiving 212 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Trissia Brown United States	5	115	106	46	45	32	5	220
David Romo‐Bucheli Colombia	6	232 2.0×	179 1.7×	43 0.9×	39 0.9×	42 1.3×	13	327
Venkata N. P. Vemuri United States	4	98 0.9×	143 1.3×	91 2.0×	51 1.1×	75 2.3×	6	305
Saman Farahmand United States	6	133 1.2×	162 1.5×	88 1.9×	65 1.4×	32 1.0×	11	308
Igor Odintsov United States	5	98 0.9×	143 1.3×	40 0.9×	37 0.8×	24 0.8×	15	260
Chiara Maria Lavinia Loeffler Germany	8	112 1.0×	108 1.0×	43 0.9×	73 1.6×	24 0.8×	12	240
Can Koyuncu United States	10	106 0.9×	123 1.2×	30 0.7×	62 1.4×	73 2.3×	21	253
Heather D. Couture United States	5	155 1.3×	215 2.0×	36 0.8×	38 0.8×	54 1.7×	7	276
Zhaoyang Xu China	6	133 1.2×	164 1.5×	23 0.5×	30 0.7×	27 0.8×	16	221
Ronnachai Jaroensri United States	5	151 1.3×	200 1.9×	44 1.0×	57 1.3×	24 0.8×	7	328
Lorraine Corsale United States	6	124 1.1×	237 2.2×	25 0.5×	64 1.4×	49 1.5×	6	301

Countries citing papers authored by Trissia Brown

Since Specialization

Citations

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

Fields of papers citing papers by Trissia Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Trissia Brown

This figure shows the co-authorship network connecting the top 25 collaborators of Trissia Brown. A scholar is included among the top collaborators of Trissia Brown 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 Trissia Brown. Trissia Brown 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.

Krogue, Justin D., Shekoofeh Azizi, Fraser Elisabeth Tan, et al.. (2023). Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning. SHILAP Revista de lepidopterología. 3(1). 59–59. 12 indexed citations

2.

Sadhwani, Apaar, Ali Behrooz, Trissia Brown, et al.. (2021). Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images. Scientific Reports. 11(1). 16605–16605. 34 indexed citations

3.

Gamble, Paul, Ronnachai Jaroensri, Hongwu Wang, et al.. (2021). Determining breast cancer biomarker status and associated morphological features using deep learning. Communications Medicine. 1(1). 14–14. 86 indexed citations

4.

Kohlberger, Timo, Yun Liu, Melissa Moran, et al.. (2019). Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection. Journal of Pathology Informatics. 10(1). 39–39. 61 indexed citations

5.

Negendank, William, Trissia Brown, Jeffrey L. Evelhoch, et al.. (1992). Proceedings of a National Cancer Institute workshop: MR spectroscopy and tumor cell biology.. Radiology. 185(3). 875–883. 27 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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