Heming Yao

483 total citations
25 papers, 323 citations indexed

About

Heming Yao is a scholar working on Analytical Chemistry, Oncology and Epidemiology. According to data from OpenAlex, Heming Yao has authored 25 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Analytical Chemistry, 5 papers in Oncology and 5 papers in Epidemiology. Recurrent topics in Heming Yao's work include Spectroscopy and Chemometric Analyses (6 papers), Colorectal Cancer Screening and Detection (4 papers) and Advanced Statistical Methods and Models (3 papers). Heming Yao is often cited by papers focused on Spectroscopy and Chemometric Analyses (6 papers), Colorectal Cancer Screening and Detection (4 papers) and Advanced Statistical Methods and Models (3 papers). Heming Yao collaborates with scholars based in United States, China and Hong Kong. Heming Yao's co-authors include Jonathan Gryak, Kayvan Najarian, Ryan W. Stidham, H. Jeffrey Wilkins, Shrinivas Bishu, Akbar K. Waljee, Michael Rice, Craig A. Williamson, Yiping Du and Wanchao Chen and has published in prestigious journals such as Journal of Neuroscience, Gastroenterology and Genome biology.

In The Last Decade

Heming Yao

24 papers receiving 315 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heming Yao United States 10 88 75 59 55 49 25 323
Atsushi Goto Japan 8 43 0.5× 11 0.1× 24 0.4× 28 0.5× 77 1.6× 29 295
Xiaosong Xu China 9 37 0.4× 10 0.1× 18 0.3× 185 3.4× 54 1.1× 20 404
Florentino Luciano Caetano dos Santos Poland 10 45 0.5× 8 0.1× 12 0.2× 43 0.8× 40 0.8× 35 297
Ioannis Stathopoulos Greece 12 36 0.4× 20 0.3× 12 0.2× 50 0.9× 32 0.7× 28 404
Satadru Ray India 13 47 0.5× 9 0.1× 21 0.4× 100 1.8× 54 1.1× 25 320
Hiroyuki Ogihara Japan 8 47 0.5× 7 0.1× 6 0.1× 43 0.8× 32 0.7× 24 211
Marcelo Moreno Brazil 11 66 0.8× 5 0.1× 23 0.4× 55 1.0× 58 1.2× 43 338
Kristine Geldnere Latvia 5 52 0.6× 27 0.4× 9 0.2× 91 1.7× 29 0.6× 5 239
Anwer Siddiqi United States 11 31 0.4× 9 0.1× 23 0.4× 80 1.5× 37 0.8× 28 368
Sergio Oller Moreno Spain 10 20 0.2× 24 0.3× 13 0.2× 203 3.7× 10 0.2× 15 380

Countries citing papers authored by Heming Yao

Since Specialization
Citations

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

Fields of papers citing papers by Heming Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heming Yao

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

All Works

20 of 20 papers shown
1.
2.
Hinz, Flora I., Heming Yao, Anton Delwig, et al.. (2024). Context-Specific Stress Causes Compartmentalized SARM1 Activation and Local Degeneration in Cortical Neurons. Journal of Neuroscience. 44(24). e2424232024–e2424232024. 2 indexed citations
3.
4.
Chang, Yuan, et al.. (2024). Advancing Ton-Bag Detection in Seaport Logistics with an Enhanced YOLOv8 Algorithm. Journal of Marine Science and Engineering. 12(11). 1916–1916. 1 indexed citations
5.
Yao, Heming, Jessica R. Golbus, Jonathan Gryak, et al.. (2022). Identifying potential candidates for advanced heart failure therapies using an interpretable machine learning algorithm. The Journal of Heart and Lung Transplantation. 41(12). 1781–1789. 6 indexed citations
6.
Yao, Heming, Harm Derksen, Jessica R. Golbus, et al.. (2022). A Novel Tropical Geometry-Based Interpretable Machine Learning Method: Pilot Application to Delivery of Advanced Heart Failure Therapies. IEEE Journal of Biomedical and Health Informatics. 27(1). 239–250. 8 indexed citations
7.
Qin, Tingting, Christopher H. T. Lee, Shiting Li, et al.. (2022). Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data. Genome biology. 23(1). 105–105. 11 indexed citations
8.
Yao, Heming, Craig A. Williamson, Jonathan Gryak, & Kayvan Najarian. (2020). Automated hematoma segmentation and outcome prediction for patients with traumatic brain injury. Artificial Intelligence in Medicine. 107. 101910–101910. 33 indexed citations
9.
Yao, Heming, Kayvan Najarian, Jonathan Gryak, et al.. (2020). Fully automated endoscopic disease activity assessment in ulcerative colitis. Gastrointestinal Endoscopy. 93(3). 728–736.e1. 78 indexed citations
10.
Stidham, Ryan W., Heming Yao, Shrinivas Bishu, et al.. (2020). P595 Feasibility and performance of a fully automated endoscopic disease severity grading tool for ulcerative colitis using unaltered multisite videos. Journal of Crohn s and Colitis. 14(Supplement_1). S495–S496. 1 indexed citations
11.
Sun, Lin, Yunfei Sha, Yiping Du, et al.. (2019). Simultaneous Detection of Lutein and β-Carotene in Tobacco by Using Raman Spectroscopy Combined with Partial Least Squares. Guangpuxue yu guangpu fenxi. 39(11). 3519. 4 indexed citations
12.
Zhang, Feiyu, et al.. (2018). A new strategy of least absolute shrinkage and selection operator coupled with sampling error profile analysis for wavelength selection. Chemometrics and Intelligent Laboratory Systems. 175. 47–54. 33 indexed citations
13.
Zhang, Feiyu, et al.. (2018). A variable informative criterion based on weighted voting strategy combined with LASSO for variable selection in multivariate calibration. Chemometrics and Intelligent Laboratory Systems. 184. 132–141. 13 indexed citations
14.
15.
Yao, Heming, Craig A. Williamson, S. M. Reza Soroushmehr, Jonathan Gryak, & Kayvan Najarian. (2018). Hematoma Segmentation Using Dilated Convolutional Neural Network. PubMed. 2018. 5902–5905. 5 indexed citations
16.
Yao, Heming, et al.. (2018). Filter-Pruned 3D Convolutional Neural Network for Drowsiness Detection. PubMed. 2018. 1258–1262. 6 indexed citations
17.
Zhang, Feiyu, et al.. (2017). Sampling Error Profile Analysis for calibration transfer in multivariate calibration. Chemometrics and Intelligent Laboratory Systems. 171. 234–240. 10 indexed citations
18.
Shen, Yi, Heming Yao, Ao Li, & Minghui Wang. (2016). CSCdb: a cancer stem cells portal for markers, related genes and functional information. Database. 2016. baw023–baw023. 15 indexed citations
19.
Warner, Jeremy L., Matthew J. Rioth, Kenneth D. Mandl, et al.. (2016). SMART precision cancer medicine: a FHIR-based app to provide genomic information at the point of care. Journal of the American Medical Informatics Association. 23(4). 701–710. 53 indexed citations
20.
Yao, Heming, Ao Li, & Minghui Wang. (2015). Systematic Analysis and Prediction ofIn SituCross Talk of O-GlcNAcylation and Phosphorylation. BioMed Research International. 2015. 1–12. 9 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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