Lisha Qi

3.5k total citations
71 papers, 2.4k citations indexed

About

Lisha Qi is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Lisha Qi has authored 71 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 22 papers in Cancer Research and 20 papers in Oncology. Recurrent topics in Lisha Qi's work include Radiomics and Machine Learning in Medical Imaging (13 papers), RNA modifications and cancer (10 papers) and Cancer-related molecular mechanisms research (8 papers). Lisha Qi is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), RNA modifications and cancer (10 papers) and Cancer-related molecular mechanisms research (8 papers). Lisha Qi collaborates with scholars based in China, United States and South Africa. Lisha Qi's co-authors include Zhiyong Liu, Hua Guo, Xiulan Zhao, Baocun Sun, Yuchao He, Baocun Sun, Wenfeng Cao, Wangzhao Song, Ning Zhang and Xue Leng and has published in prestigious journals such as Gastroenterology, Scientific Reports and The FASEB Journal.

In The Last Decade

Lisha Qi

69 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lisha Qi China 28 1.4k 893 585 415 221 71 2.4k
Julia Beretov Australia 25 1.3k 0.9× 926 1.0× 858 1.5× 410 1.0× 207 0.9× 51 2.4k
Guanzhen Yu China 27 1.5k 1.1× 763 0.9× 532 0.9× 341 0.8× 147 0.7× 81 2.3k
Niklas Rindtorff Germany 5 1.8k 1.2× 564 0.6× 725 1.2× 231 0.6× 224 1.0× 6 2.6k
Kaoru Mogushi Japan 29 1.6k 1.2× 799 0.9× 756 1.3× 491 1.2× 101 0.5× 93 2.7k
Yi‐Wu Dang China 26 1.7k 1.2× 1.4k 1.6× 422 0.7× 367 0.9× 98 0.4× 133 2.5k
Ruth Birbe United States 29 1.5k 1.1× 1.1k 1.3× 707 1.2× 427 1.0× 94 0.4× 50 2.7k
Hao Wen China 26 981 0.7× 517 0.6× 453 0.8× 274 0.7× 202 0.9× 103 2.1k
Laura Annaratone Italy 27 1.1k 0.8× 787 0.9× 688 1.2× 269 0.6× 233 1.1× 68 2.2k
Sherry X. Yang United States 21 1.8k 1.3× 904 1.0× 1.5k 2.5× 372 0.9× 299 1.4× 54 3.2k
Xi Jin China 26 1.3k 0.9× 1.0k 1.1× 775 1.3× 668 1.6× 117 0.5× 83 2.5k

Countries citing papers authored by Lisha Qi

Since Specialization
Citations

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

Fields of papers citing papers by Lisha Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lisha Qi

This figure shows the co-authorship network connecting the top 25 collaborators of Lisha Qi. A scholar is included among the top collaborators of Lisha Qi 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 Lisha Qi. Lisha Qi 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
2.
Qi, Lisha, Xiaoli Li, Yong Yang, et al.. (2024). Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis. Clinical Radiology. 79(7). 501–514. 1 indexed citations
3.
Liu, Weishuai, Xiaozhou Yu, Yixing Feng, et al.. (2022). CD73, a Promising Therapeutic Target of Diclofenac, Promotes Metastasis of Pancreatic Cancer through a Nucleotidase Independent Mechanism. Advanced Science. 10(6). e2206335–e2206335. 22 indexed citations
4.
Wang, Chao, Jingjing Zhou, Lili Wang, et al.. (2022). ABOblood groups and expression of blood group antigens of epithelial ovarian cancer in Chinese women. Cancer Medicine. 12(6). 7498–7507. 3 indexed citations
5.
Li, Chunxiang, Jinghan Li, Lisha Qi, et al.. (2022). An Ultrasonic-Based Radiomics Nomogram for Distinguishing Between Benign and Malignant Solid Renal Masses. Frontiers in Oncology. 12. 847805–847805. 4 indexed citations
6.
Cui, Xiaonan, Lei Zheng, Wenjuan Ma, et al.. (2022). Prognostic value of desmoplastic stromal reaction, tumor budding and tumor-stroma ratio in stage II colorectal cancer. Journal of Gastrointestinal Oncology. 13(6). 2903–2921. 10 indexed citations
7.
Yi, Xianfu, Lu Chen, Ti Zhang, et al.. (2021). Single-Cell DNA Sequencing Reveals Punctuated and Gradual Clonal Evolution in Hepatocellular Carcinoma. Gastroenterology. 162(1). 238–252. 45 indexed citations
8.
Wang, Yutong, Ziqian Zeng, Mingshuang Tang, et al.. (2020). Sex Disparities in the Clinical Characteristics, Synchronous Distant Metastasis Occurrence and Prognosis: A Pan-cancer Analysis. Journal of Cancer. 12(2). 498–507. 8 indexed citations
9.
Zhang, Wenshuai, Lisha Qi, Lu Cao, et al.. (2020). ISG15 induces ESRP1 to inhibit lung adenocarcinoma progression. Cell Death and Disease. 11(7). 511–511. 21 indexed citations
10.
Chen, Lu, Xianfu Yi, Hua Guo, et al.. (2020). The role of bone marrow-derived cells in the origin of liver cancer revealed by single-cell sequencing. Cancer Biology and Medicine. 17(1). 142–153. 10 indexed citations
11.
Chen, Lu, Dongming Liu, Xianfu Yi, et al.. (2020). The novel miR-1269b-regulated protein SVEP1 induces hepatocellular carcinoma proliferation and metastasis likely through the PI3K/Akt pathway. Cell Death and Disease. 11(5). 320–320. 32 indexed citations
12.
Lara, Olivia D., Zhihui Wang, Sara Corvigno, et al.. (2019). Tumor core biopsies adequately represent immune microenvironment of high-grade serous carcinoma. Scientific Reports. 9(1). 17589–17589. 16 indexed citations
13.
Shen, Weiwei, Na Niu, Lisha Qi, et al.. (2019). GATA6: a new predictor for prognosis in ovarian cancer. Human Pathology. 86. 163–169. 19 indexed citations
14.
Chen, Lu, Yuchao He, Ziye Chen, et al.. (2018). HCC-derived exosomes elicit HCC progression and recurrence by epithelial-mesenchymal transition through MAPK/ERK signalling pathway. Cell Death and Disease. 9(5). 513–513. 192 indexed citations
15.
Ma, Wenjuan, et al.. (2018). Breast cancer Ki67 expression prediction by DCE-MRI radiomics features. Clinical Radiology. 73(10). 909.e1–909.e5. 79 indexed citations
16.
Cao, Lu, Lisha Qi, Lin Zhang, et al.. (2017). Human nonsense-mediated RNA decay regulates EMT by targeting the TGF-ß signaling pathway in lung adenocarcinoma. Cancer Letters. 403. 246–259. 40 indexed citations
17.
Xue, Ruidong, Ruoyan Li, Hua Guo, et al.. (2016). Variable Intra-Tumor Genomic Heterogeneity of Multiple Lesions in Patients With Hepatocellular Carcinoma. Gastroenterology. 150(4). 998–1008. 165 indexed citations
19.
Qi, Lisha, et al.. (2014). Wnt3a expression is associated with epithelial-mesenchymal transition and promotes colon cancer progression. Journal of Experimental & Clinical Cancer Research. 33(1). 107–107. 99 indexed citations
20.
Liu, Yan, Fei Zhang, Xiaofang Zhang, et al.. (2012). Expression of Nucleophosmin/NPM1 correlates with migration and invasiveness of colon cancer cells. Journal of Biomedical Science. 19(1). 53–53. 60 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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