Hong‐Li Hua

460 total citations
18 papers, 306 citations indexed

About

Hong‐Li Hua is a scholar working on Otorhinolaryngology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hong‐Li Hua has authored 18 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Otorhinolaryngology, 7 papers in Molecular Biology and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hong‐Li Hua's work include Radiomics and Machine Learning in Medical Imaging (6 papers), Head and Neck Cancer Studies (6 papers) and RNA and protein synthesis mechanisms (5 papers). Hong‐Li Hua is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), Head and Neck Cancer Studies (6 papers) and RNA and protein synthesis mechanisms (5 papers). Hong‐Li Hua collaborates with scholars based in China, Ethiopia and United States. Hong‐Li Hua's co-authors include Feng‐Biao Guo, Chuan Dong, Song Li, Yuqin Deng, Zezhang Tao, Shuo Liu, Zhiling Zhu, Nini Rao, Jian Huang and Guoshi Chai and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and BioMed Research International.

In The Last Decade

Hong‐Li Hua

17 papers receiving 304 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hong‐Li Hua China 10 205 54 44 33 27 18 306
Chuan-Yi Tang Taiwan 7 202 1.0× 13 0.2× 7 0.2× 15 0.5× 19 0.7× 11 344
Nathan LaPierre United States 8 140 0.7× 4 0.1× 14 0.3× 23 0.7× 3 0.1× 17 241
Wanwan Hou China 9 100 0.5× 2 0.0× 9 0.2× 13 0.4× 10 0.4× 23 195
Eric Wilson United States 6 53 0.3× 10 0.2× 7 0.2× 5 0.2× 6 0.2× 11 143
Ahmad Malik Canada 4 153 0.7× 9 0.2× 7 0.2× 2 0.1× 7 0.3× 5 260
JaeJin Choi South Korea 8 126 0.6× 3 0.1× 6 0.1× 29 0.9× 8 0.3× 9 219
Luwen Ning China 8 188 0.9× 2 0.0× 8 0.2× 16 0.5× 19 0.7× 8 242
Siji Nian China 11 104 0.5× 43 1.0× 28 0.8× 15 0.6× 29 287
Hassaan Maan Canada 7 314 1.5× 28 0.6× 19 0.6× 9 0.3× 9 480
Sharmila Sambanthamoorthy United States 4 103 0.5× 12 0.3× 24 0.7× 6 0.2× 4 294

Countries citing papers authored by Hong‐Li Hua

Since Specialization
Citations

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

Fields of papers citing papers by Hong‐Li Hua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong‐Li Hua. 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 Hong‐Li Hua. The network helps show where Hong‐Li Hua may publish in the future.

Co-authorship network of co-authors of Hong‐Li Hua

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

All Works

18 of 18 papers shown
1.
2.
Hua, Hong‐Li, Yuqin Deng, Yuchen Tang, et al.. (2023). Inflammatory endotypes of adenoidal hypertrophy based on a cluster analysis of biomarkers. International Immunopharmacology. 127. 111318–111318. 2 indexed citations
3.
Li, Song, Xia Wan, Yuqin Deng, et al.. (2023). Predicting prognosis of nasopharyngeal carcinoma based on deep learning: peritumoral region should be valued. Cancer Imaging. 23(1). 14–14. 10 indexed citations
4.
Hua, Hong‐Li, Song Li, Huan Huang, et al.. (2023). Deep learning for the prediction of residual tumor after radiotherapy and treatment decision-making in patients with nasopharyngeal carcinoma based on magnetic resonance imaging. Quantitative Imaging in Medicine and Surgery. 13(6). 3569–3586. 3 indexed citations
5.
Hua, Hong‐Li, Song Li, Yu Xu, et al.. (2022). Differentiation of eosinophilic and non‐eosinophilic chronic rhinosinusitis on preoperative computed tomography using deep learning. Clinical Otolaryngology. 48(2). 330–338. 11 indexed citations
6.
Li, Song, Yuqin Deng, Hong‐Li Hua, et al.. (2022). Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI. Computer Methods and Programs in Biomedicine. 219. 106785–106785. 11 indexed citations
7.
Hua, Hong‐Li, et al.. (2022). Deep Learning for Predicting Distant Metastasis in Patients with NasopharyngealCarcinoma Based on Pre-Radiotherapy Magnetic ResonanceImaging. Combinatorial Chemistry & High Throughput Screening. 26(7). 1351–1363. 3 indexed citations
8.
Li, Song, Hong‐Li Hua, Fen Li, et al.. (2022). Anatomical Partition‐Based Deep Learning: An Automatic Nasopharyngeal MRI Recognition Scheme. Journal of Magnetic Resonance Imaging. 56(4). 1220–1229. 7 indexed citations
9.
Li, Song, et al.. (2021). The association between allergy and sinusitis: a cross-sectional study based on NHANES 2005–2006. Allergy Asthma and Clinical Immunology. 17(1). 135–135. 7 indexed citations
10.
Li, Song, Yuqin Deng, Zhiling Zhu, Hong‐Li Hua, & Zezhang Tao. (2021). A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging. Diagnostics. 11(9). 1523–1523. 36 indexed citations
11.
12.
Dong, Chuan, et al.. (2018). Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment. Briefings in Bioinformatics. 21(1). 171–181. 27 indexed citations
13.
Guo, Feng‐Biao, Chuan Dong, Hong‐Li Hua, et al.. (2017). Accurate prediction of human essential genes using only nucleotide composition and association information. Bioinformatics. 33(12). 1758–1764. 46 indexed citations
14.
Dong, Chuan, Ge‐Fei Hao, Hong‐Li Hua, et al.. (2017). Anti-CRISPRdb: a comprehensive online resource for anti-CRISPR proteins. Nucleic Acids Research. 46(D1). D393–D398. 61 indexed citations
15.
Gao, Yi‐Zhou, et al.. (2017). Metabolic pathway databases and model repositories. Quantitative Biology. 6(1). 30–39. 9 indexed citations
16.
Dong, Chuan, Hong‐Li Hua, Yuan‐Nong Ye, et al.. (2016). Combining pseudo dinucleotide composition with the Z curve method to improve the accuracy of predicting DNA elements: a case study in recombination spots. Molecular BioSystems. 12(9). 2893–2900. 18 indexed citations
17.
Hua, Hong‐Li, et al.. (2016). An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms. BioMed Research International. 2016. 1–9. 17 indexed citations
18.
Wei, Wen, Feng Gao, Meng‐Ze Du, et al.. (2016). Zisland Explorer: detect genomic islands by combining homogeneity and heterogeneity properties. Briefings in Bioinformatics. 18(3). bbw019–bbw019. 36 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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