Rachel Howard

960 total citations
20 papers, 555 citations indexed

About

Rachel Howard is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Rachel Howard has authored 20 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Rachel Howard's work include Biomedical Text Mining and Ontologies (3 papers), Adipose Tissue and Metabolism (3 papers) and BRCA gene mutations in cancer (2 papers). Rachel Howard is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Adipose Tissue and Metabolism (3 papers) and BRCA gene mutations in cancer (2 papers). Rachel Howard collaborates with scholars based in United States, United Kingdom and Canada. Rachel Howard's co-authors include Peter A. Kanetsky, Kathleen M. Egan, M J Holness, M C Sugden, Gideon P. Smith, Mary C. Sugden, Mark J. Holness, Michael R. Munday, Dana E. Rollison and David J. Lythgoe and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cancer Research and Scientific Reports.

In The Last Decade

Rachel Howard

19 papers receiving 551 citations

Peers

Rachel Howard

ONCOL

PHYSI

SURGE

PRM

Sujata Narayanan United States

Lixia Zhu China

Rasmus Røge Denmark

Aline Maillard France

S. M. Qasim Hussaini United States

Amandeep Mann United States

Laurence M. Black United States

Pallav Bhatnagar United States

Susana Hernández Spain

Guoqiang Xu China

Sujata Narayanan United States

Rachel Howard

163 ×0.9

ONCOL

83 ×1.1

PHYSI

74 ×1.1

SURGE

159 ×2.6

PRM

Citations per year, relative to Rachel Howard Rachel Howard (= 1×) peers Sujata Narayanan

Countries citing papers authored by Rachel Howard

Since Specialization

Citations

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

Fields of papers citing papers by Rachel Howard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rachel Howard

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

Howard, Rachel, et al.. (2023). Assessing the Contribution of Scanned Outside Documents to the Completeness of Real-World Data Abstraction. JCO Clinical Cancer Informatics. 7(7). e2200118–e2200118. 3 indexed citations

Rollison, Dana E., Brian D. Gonzalez, Kea Turner, et al.. (2023). Examining disparities in large‐scale patient‐reported data capture using digital tools among cancer patients at clinical intake. Cancer Medicine. 12(18). 19033–19046. 7 indexed citations

Howard, Rachel, Patricia Lewis, Rodrigo Carvajal, et al.. (2023). Abstract 2068: MCAP Explore: A self-service data exploration and cohort building tool for oncologists. Cancer Research. 83(7_Supplement). 2068–2068.

Mitchell, J. Ross, et al.. (2021). A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study. Journal of Medical Internet Research. 24(3). e27210–e27210. 22 indexed citations

Hicks, J. Kevin, Rachel Howard, Jacob J. Adashek, et al.. (2021). Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice. JCO Precision Oncology. 5(5). 884–895. 31 indexed citations

Turner, Kea, Naomi C. Brownstein, Zachary Thompson, et al.. (2021). Longitudinal patient-reported outcomes and survival among early-stage non-small cell lung cancer patients receiving stereotactic body radiotherapy. Radiotherapy and Oncology. 167. 116–121. 6 indexed citations

Howard, Rachel & Gideon P. Smith. (2020). Treatment of calcinosis cutis with sodium thiosulfate therapy. Journal of the American Academy of Dermatology. 83(5). 1518–1520. 17 indexed citations

Mitchell, Ross, et al.. (2020). Abstract 2101: Deep learning for automatic extraction of tumor site and histology from unstructured pathology reports. Cancer Research. 80(16_Supplement). 2101–2101. 2 indexed citations

Howard, Rachel, et al.. (2019). Sociodemographic and lifestyle factors associated with the neutrophil-to-lymphocyte ratio. Annals of Epidemiology. 38. 11–21.e6. 56 indexed citations

10.

Howard, Rachel, et al.. (2019). Cytoplasmic convection currents and intracellular temperature gradients. PLoS Computational Biology. 15(11). e1007372–e1007372. 17 indexed citations

11.

Howard, Rachel, Peter A. Kanetsky, & Kathleen M. Egan. (2019). Exploring the prognostic value of the neutrophil-to-lymphocyte ratio in cancer. Scientific Reports. 9(1). 19673–19673. 203 indexed citations

12.

Tetreault, Lindsay, Rachel Howard, Alpesh A. Patel, et al.. (2019). The discrepancy between functional outcome and self-reported health status after surgery for degenerative cervical myelopathy. The Spine Journal. 19(11). 1809–1815. 7 indexed citations

13.

Suzuki, Oscar, et al.. (2019). Characterizing the Pharmacogenome using Molecular Inversion Probes for Targeted Next-Generation Sequencing. Pharmacogenomics. 20(14). 1005–1020. 7 indexed citations

14.

Howard, Rachel, Sameer Al Diffalha, José M. Pimiento, et al.. (2018). CD133 Expression as a Helicobacter pylori-independent Biomarker of Gastric Cancer Progression. Anticancer Research. 38(8). 4443–4448. 7 indexed citations

15.

Suzuki, Oscar, et al.. (2018). Implementing Clinical Pharmacogenomics in the Classroom: Student Pharmacist Impressions of an Educational Intervention Including Personal Genotyping. SHILAP Revista de lepidopterología. 6(4). 115–115. 18 indexed citations

16.

Schweizer, Susanne, Lauren Navrady, Rachel Howard, et al.. (2017). Affective enhancement of working memory is maintained in depression.. Emotion. 18(1). 127–137. 12 indexed citations

17.

Egerton, Alice, James Stone, Christopher A. Chaddock, et al.. (2014). Relationship Between Brain Glutamate Levels and Clinical Outcome in Individuals at Ultra High Risk of Psychosis. Neuropsychopharmacology. 39(12). 2891–2899. 72 indexed citations

18.

Sugden, Mary C., Rachel Howard, Michael R. Munday, & Mark J. Holness. (1993). Mechanisms involved in the coordinate regulation of strategic enzymes of glucose metabolism. Advances in Enzyme Regulation. 33. 71–95. 30 indexed citations

19.

Howard, Rachel, Karen A. Orfali, & Mary C. Sugden. (1993). Effects of diet and hormonal status on brown fat lipoprotein lipase activity. Biochemical Society Transactions. 21(3). 310S–310S. 3 indexed citations

20.

Sugden, M C, M J Holness, & Rachel Howard. (1993). Changes in lipoprotein lipase activities in adipose tissue, heart and skeletal muscle during continuous or interrupted feeding. Biochemical Journal. 292(1). 113–119. 35 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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