Roy Harnish

1.0k total citations · 1 hit paper
14 papers, 721 citations indexed

About

Roy Harnish is a scholar working on Radiology, Nuclear Medicine and Imaging, Orthopedics and Sports Medicine and Surgery. According to data from OpenAlex, Roy Harnish has authored 14 papers receiving a total of 721 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Orthopedics and Sports Medicine and 4 papers in Surgery. Recurrent topics in Roy Harnish's work include Bone health and osteoporosis research (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and MRI in cancer diagnosis (3 papers). Roy Harnish is often cited by papers focused on Bone health and osteoporosis research (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and MRI in cancer diagnosis (3 papers). Roy Harnish collaborates with scholars based in United States, Iceland and China. Roy Harnish's co-authors include Benjamin L. Franc, Youngho Seo, Spencer C. Behr, Timothy P. Copeland, Shih-Ying Huang, Carina Marí Aparici, Thomas Lang, Miguel Hernandez Pampaloni, Michael Kawczynski and Kelly A. Zalocusky and has published in prestigious journals such as Radiology, Journal of Bone and Mineral Research and Bone.

In The Last Decade

Roy Harnish

14 papers receiving 707 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using ¹⁸F-FDG PET of the Brain

2018 379 citations Yiming Ding, Jae Ho Sohn et al. Radiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Roy Harnish United States	11	296	178	162	124	117	14	721
Karteek Popuri Canada	21	330 1.1×	21 0.1×	155 1.0×	108 0.9×	114 1.0×	69	1.4k
Ein Oh South Korea	12	152 0.5×	53 0.3×	37 0.2×	62 0.5×	46 0.4×	14	524
Walter F. Wiggins United States	14	173 0.6×	23 0.1×	56 0.3×	103 0.8×	124 1.1×	43	595
Bahram Mohajer Iran	13	203 0.7×	36 0.2×	40 0.2×	119 1.0×	91 0.8×	33	660
Khaled Abdel‐Aziz United Kingdom	15	129 0.4×	18 0.1×	51 0.3×	55 0.4×	34 0.3×	26	764
Chuanfu Li China	18	513 1.7×	17 0.1×	31 0.2×	155 1.3×	48 0.4×	88	1.2k
Francesco Grussu United Kingdom	16	701 2.4×	162 0.9×	32 0.2×	43 0.3×	40 0.3×	48	943
Lara Harrison Finland	11	294 1.0×	123 0.7×	75 0.5×	66 0.5×	68 0.6×	14	560
Shahriar Faghani United States	16	297 1.0×	7 0.0×	141 0.9×	111 0.9×	130 1.1×	57	680
Gian Marco Conte United States	15	413 1.4×	15 0.1×	92 0.6×	27 0.2×	93 0.8×	35	691

Countries citing papers authored by Roy Harnish

Since Specialization

Citations

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

Fields of papers citing papers by Roy Harnish

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roy Harnish

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

All Works

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14 of 14 papers shown

Arasu, Vignesh A., Wen Li, Fredrik Strand, et al.. (2020). Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2− Patients. Journal of Breast Imaging. 2(4). 352–360. 10 indexed citations

Huang, Shih-Ying, Benjamin L. Franc, Roy Harnish, et al.. (2018). Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis. npj Breast Cancer. 4(1). 24–24. 77 indexed citations

Ding, Yiming, Jae Ho Sohn, Michael Kawczynski, et al.. (2018). A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using ¹⁸F-FDG PET of the Brain. Radiology. 290(2). 456–464. 379 indexed citations breakdown →

Lituiev, Dmytro, Hari Trivedi, Maryam Panahiazar, et al.. (2018). Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers. Journal of Digital Imaging. 32(2). 228–233. 3 indexed citations

Arentson‐Lantz, Emily, Isra Saeed, Lynda Frassetto, et al.. (2017). 11C-L-methyl methionine dynamic PET/CT of skeletal muscle: response to protein supplementation compared to L-[ring 13C6] phenylalanine infusion with serial muscle biopsy. Annals of Nuclear Medicine. 31(4). 295–303. 1 indexed citations

Wilmes, Lisa J., Wen Li, Hee Jung Shin, et al.. (2016). Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients with Breast Cancer. Tomography. 2(4). 438–447. 12 indexed citations

Heilmeier, Ursula, Janina Patsch, Roy Harnish, et al.. (2015). Volumetric femoral BMD, bone geometry, and serum sclerostin levels differ between type 2 diabetic postmenopausal women with and without fragility fractures. Osteoporosis International. 26(4). 1283–1293. 52 indexed citations

Carballido‐Gamio, Julio, Serena Bonaretti, Isra Saeed, et al.. (2015). Automatic multi-parametric quantification of the proximal femur with quantitative computed tomography.. PubMed. 5(4). 552–68. 33 indexed citations

Harnish, Roy, Sven Prevrhal, Abass Alavi, Habib Zaidi, & Thomas Lang. (2014). The effect of metal artefact reduction on CT-based attenuation correction for PET imaging in the vicinity of metallic hip implants: a phantom study. Annals of Nuclear Medicine. 28(6). 540–550. 10 indexed citations

10.

Carballido‐Gamio, Julio, Roy Harnish, Isra Saeed, et al.. (2013). Structural patterns of the proximal femur in relation to age and hip fracture risk in women. Bone. 57(1). 290–299. 33 indexed citations

11.

Lang, Thomas, Isra Saeed, T. Streeper, et al.. (2013). Spatial Heterogeneity in the Response of the Proximal Femur to Two Lower-Body Resistance Exercise Regimens. Journal of Bone and Mineral Research. 29(6). 1337–1345. 32 indexed citations

12.

Harnish, Roy, T. Streeper, & Isra Saeed. (2012). Quantification of Changes in Skeletal Muscle Amino Acid Kinetics in Adult Humans in Response to Exercise via Positron-emission Tomography with L-[methyl-11C] methionine. 2(1). 2 indexed citations

13.

Carballido‐Gamio, Julio, Roy Harnish, Isra Saeed, et al.. (2012). Proximal femoral density distribution and structure in relation to age and hip fracture risk in women. Journal of Bone and Mineral Research. 28(3). 537–546. 60 indexed citations

14.

Prevrhal, Sven, et al.. (2011). CT Angiographic Measurement of Vascular Blood Flow Velocity by Using Projection Data. Radiology. 261(3). 923–929. 17 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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