Jui Lan

1.3k total citations
42 papers, 912 citations indexed

About

Jui Lan is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Surgery. According to data from OpenAlex, Jui Lan has authored 42 papers receiving a total of 912 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Pulmonary and Respiratory Medicine, 15 papers in Oncology and 8 papers in Surgery. Recurrent topics in Jui Lan's work include Sarcoma Diagnosis and Treatment (13 papers), Endometrial and Cervical Cancer Treatments (6 papers) and Oral and Maxillofacial Pathology (5 papers). Jui Lan is often cited by papers focused on Sarcoma Diagnosis and Treatment (13 papers), Endometrial and Cervical Cancer Treatments (6 papers) and Oral and Maxillofacial Pathology (5 papers). Jui Lan collaborates with scholars based in Taiwan and United Kingdom. Jui Lan's co-authors include Chien‐Feng Li, Hsuan‐Ying Huang, Huichun Tai, Yu‐Chien Kao, Shih‐Chiang Huang, I‐Chieh Chuang, Shih-Chen Yu, Po‐Chun Lin, Hsuan-Ying Huang and Fu-Min Fang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Jui Lan

38 papers receiving 901 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jui Lan Taiwan 17 385 294 233 226 192 42 912
Umio Yamaguchi Japan 18 573 1.5× 249 0.8× 214 0.9× 239 1.1× 53 0.3× 28 1.0k
Robert Nakayama Japan 21 829 2.2× 303 1.0× 697 3.0× 496 2.2× 40 0.2× 82 1.6k
Emiel Ruijter Netherlands 12 545 1.4× 192 0.7× 234 1.0× 112 0.5× 49 0.3× 17 835
Helene Geddert Germany 26 491 1.3× 367 1.2× 666 2.9× 552 2.4× 185 1.0× 49 1.7k
Juan‐Miguel Mosquera United States 10 577 1.5× 367 1.2× 374 1.6× 513 2.3× 126 0.7× 11 1.3k
Paulo Antônio Silvestre de Faria Brazil 19 587 1.5× 139 0.5× 714 3.1× 277 1.2× 44 0.2× 58 1.3k
Yvonne Schrage Netherlands 15 577 1.5× 407 1.4× 126 0.5× 240 1.1× 131 0.7× 52 820
Yu Jin Kim South Korea 18 328 0.9× 95 0.3× 326 1.4× 298 1.3× 51 0.3× 39 974
Mary Lou Keohan United States 12 672 1.7× 98 0.3× 114 0.5× 492 2.2× 26 0.1× 22 923
Henrik Lilljebjörn Sweden 22 251 0.7× 184 0.6× 588 2.5× 338 1.5× 32 0.2× 51 1.6k

Countries citing papers authored by Jui Lan

Since Specialization
Citations

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

Fields of papers citing papers by Jui Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jui Lan

This figure shows the co-authorship network connecting the top 25 collaborators of Jui Lan. A scholar is included among the top collaborators of Jui Lan 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 Jui Lan. Jui Lan 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.
Huang, Yu-Sheng, Yu‐Che Ou, Chen‐Hsuan Wu, et al.. (2024). A comparative analysis of MMR immunohistochemistry panels: Evaluating the utility of four-protein versus two-protein panels in endometrial cancer patients. Journal of the Formosan Medical Association. 124(9). 845–851.
2.
Chen, Tsung‐Hsing, et al.. (2024). Artificial Intelligence Model for a Distinction between Early-Stage Gastric Cancer Invasive Depth T1a and T1b. Journal of Cancer. 15(10). 3085–3094. 6 indexed citations
3.
Wu, Chen‐Hsuan, Hung‐Chun Fu, Yu‐Che Ou, et al.. (2024). How Progesterone Receptor Expression Impacts Platinum Sensitivity in Ovarian Clear Cell Carcinoma: Insights from Clinical and Experimental Perspectives. International Journal of Molecular Sciences. 25(14). 7942–7942. 1 indexed citations
4.
5.
Liu, Chien-Ting, Hao Lin, Yung‐Cheng Huang, et al.. (2022). Case report: Durable response after pembrolizumab in combination with radiation - induced abscopal effect in platinum - refractory metastatic endometrial clear cell carcinoma. Frontiers in Immunology. 13. 1079253–1079253. 5 indexed citations
6.
7.
Huang, Shih‐Chiang, Chi‐Chung Chen, Jui Lan, et al.. (2022). Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings. Nature Communications. 13(1). 3347–3347. 37 indexed citations
8.
Wang, Chin‐Chou, Kuo‐Tung Huang, Huang‐Chih Chang, et al.. (2021). Comprehensive analysis of PD‐L1 in non‐small cell lung cancer with emphasis on survival benefit, impact of driver mutation and histological types, and archival tissue. Thoracic Cancer. 13(1). 38–47. 7 indexed citations
9.
Ma, Ming‐Chun, Tai‐Jan Chiu, Jui Lan, et al.. (2018). Positive expression of Midkine predicts early recurrence and poor prognosis of initially resectable combined hepatocellular cholangiocarcinoma. BMC Cancer. 18(1). 227–227. 15 indexed citations
10.
Rau, Kun‐Ming, Po‐Hui Chiang, Ming-Tse Sung, et al.. (2018). Impact of Prognostic Nutritional Index on Overall Survival for Patients with Metastatic Urothelial Carcinoma. Journal of Cancer. 9(14). 2466–2471. 13 indexed citations
11.
Su, Yu‐Li, Po‐Hui Chiang, Ming-Tse Sung, et al.. (2017). Novel Inflammation-Based Prognostic Score for Predicting Survival in Patients with Metastatic Urothelial Carcinoma. PLoS ONE. 12(1). e0169657–e0169657. 10 indexed citations
12.
Liau, Jau‐Yu, Jia‐Huei Tsai, Wenchang Huang, et al.. (2017). BRAF and KRAS mutations in tubular apocrine adenoma and papillary eccrine adenoma of the skin. Human Pathology. 73. 59–65. 19 indexed citations
13.
14.
Liau, Jau‐Yu, Jui Lan, Jin‐Bon Hong, et al.. (2016). Frequent PIK3CA-activating mutations in hidradenoma papilliferums. Human Pathology. 55. 57–62. 16 indexed citations
15.
Lan, Jui, Yi‐Hsien Chen, Wei‐Chih Chen, et al.. (2016). Primary paranasal sinus clear cell carcinoma with EWSR1-ATF1 fusion: report of 2 molecularly confirmed cases exhibiting unique histopathology. Human Pathology. 63. 139–143. 12 indexed citations
16.
Tai, Huichun, I‐Chieh Chuang, Tse‐Ching Chen, et al.. (2015). NAB2–STAT6 fusion types account for clinicopathological variations in solitary fibrous tumors. Modern Pathology. 28(10). 1324–1335. 112 indexed citations
17.
Li, Chien‐Feng, Fu-Min Fang, Jui Lan, et al.. (2014). AMACR Amplification in Myxofibrosarcomas: A Mechanism of Overexpression That Promotes Cell Proliferation with Therapeutic Relevance. Clinical Cancer Research. 20(23). 6141–6152. 34 indexed citations
18.
Huang, Hsuan-Ying, Wen-Ren Wu, Yu-Hui Wang, et al.. (2013). ASS1 as a Novel Tumor Suppressor Gene in Myxofibrosarcomas: Aberrant Loss via Epigenetic DNA Methylation Confers Aggressive Phenotypes, Negative Prognostic Impact, and Therapeutic Relevance. Clinical Cancer Research. 19(11). 2861–2872. 118 indexed citations
19.
Lan, Jui, Huichun Tai, Sung‐Wei Lee, et al.. (2013). Deficiency in expression and epigenetic DNA Methylation of ASS1 gene in nasopharyngeal carcinoma: negative prognostic impact and therapeutic relevance. Tumor Biology. 35(1). 161–169. 52 indexed citations
20.
Li, Chien‐Feng, Ju-Ming Wang, Hong‐Yo Kang, et al.. (2012). Characterization of Gene Amplification–Driven SKP2 Overexpression in Myxofibrosarcoma: Potential Implications in Tumor Progression and Therapeutics. Clinical Cancer Research. 18(6). 1598–1610. 39 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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