Lili He

507 total citations
23 papers, 349 citations indexed

About

Lili He is a scholar working on Pediatrics, Perinatology and Child Health, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Lili He has authored 23 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Pediatrics, Perinatology and Child Health, 5 papers in Artificial Intelligence and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Lili He's work include Neonatal and fetal brain pathology (9 papers), Fetal and Pediatric Neurological Disorders (4 papers) and Infant Development and Preterm Care (3 papers). Lili He is often cited by papers focused on Neonatal and fetal brain pathology (9 papers), Fetal and Pediatric Neurological Disorders (4 papers) and Infant Development and Preterm Care (3 papers). Lili He collaborates with scholars based in United States and China. Lili He's co-authors include Nehal A. Parikh, Samuel K. Powell, Christopher R. Pierson, Katrina Burson, Dushyant V. Sahani, W.C. Karl, Synho Do, Homer Pien, Leo Hochhäuser and Hailong Li and has published in prestigious journals such as PLoS ONE, NeuroImage and IEEE Transactions on Medical Imaging.

In The Last Decade

Lili He

21 papers receiving 341 citations

Peers

Lili He

PPCH

CVPR

RNMI

Nicolas Wiest-Daesslé France

Michel Kocher Switzerland

Junshen Xu United States

Robert Peharz Austria

Tim McGraw United States

Claudia E. Rodriguez-Carranza United States

Daniele Perrone Netherlands

Ziyang Wang United Kingdom

S. R. Nirmala India

Liyong Chen United States

Nicolas Wiest-Daesslé France

Lili He

43 ×0.3

PPCH

198 ×1.5

CVPR

283 ×2.2

RNMI

66 ×1.1

62 ×1.3

Citations per year, relative to Lili He Lili He (= 1×) peers Nicolas Wiest-Daesslé

Countries citing papers authored by Lili He

Since Specialization

Citations

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

Fields of papers citing papers by Lili He

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lili He

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

Ma, Yue, et al.. (2025). STL-DCSInformer-ETS: A Hybrid Model for Medium- and Long-Term Sales Forecasting of Fast-Moving Consumer Goods. Applied Sciences. 15(3). 1516–1516. 1 indexed citations

He, Lili, et al.. (2025). GLARA: A Global–Local Attention Framework for Semantic Relation Abstraction and Dynamic Preference Modeling in Knowledge-Aware Recommendation. Applied Sciences. 15(12). 6386–6386.

Zhang, Yang, et al.. (2024). A Deep Reinforcement Learning-Based Dynamic Replenishment Approach for Multi-Echelon Inventory Considering Cost Optimization. Electronics. 14(1). 66–66. 1 indexed citations

Liu, Ming, et al.. (2024). MGAFN-ISA: Multi-Granularity Attention Fusion Network for Implicit Sentiment Analysis. Electronics. 13(24). 4905–4905. 1 indexed citations

Li, Hailong, et al.. (2024). DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants. Computer Methods and Programs in Biomedicine. 257. 108479–108479. 1 indexed citations

Kline, Julia E., Venkata Sita Priyanka Illapani, Hailong Li, et al.. (2022). Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology. NeuroImage. 264. 119727–119727. 7 indexed citations

Li, Hailong, et al.. (2021). Automatic Segmentation of Diffuse White Matter Abnormality on T2-weighted Brain MR Images Using Deep Learning in Very Preterm Infants. Radiology Artificial Intelligence. 3(3). e200166–e200166. 7 indexed citations

Jiang, Yu, et al.. (2020). Analysis of Semi-supervised Text Clustering Algorithm on Marine Data. Computers, materials & continua/Computers, materials & continua (Print). 64(1). 207–216. 4 indexed citations

He, Lili, et al.. (2017). Research on Retailer Order Forecast Based on Improved Exponential Smoothing Method. 35. 1–9. 1 indexed citations

10.

He, Lili, et al.. (2017). A Binary Approximate Naive Bayesian Classification Algorithm Based on SOM Neural Network Clustering. 38. 1344–1347. 1 indexed citations

11.

He, Lili & Nehal A. Parikh. (2016). Brain functional network connectivity development in very preterm infants: The first six months. Early Human Development. 98. 29–35. 26 indexed citations

12.

He, Lili & Nehal A. Parikh. (2015). Aberrant Executive and Frontoparietal Functional Connectivity in Very Preterm Infants With Diffuse White Matter Abnormalities. Pediatric Neurology. 53(4). 330–337. 29 indexed citations

13.

Powell, Samuel K., et al.. (2014). Reliability and Repeatability of Quantitative Tractography Methods for Mapping Structural White Matter Connectivity in Preterm and Term Infants at Term-Equivalent Age. PLoS ONE. 9(1). e85807–e85807. 27 indexed citations

14.

He, Lili & Nehal A. Parikh. (2013). Atlas-Guided Quantification of White Matter Signal Abnormalities on Term-Equivalent Age MRI in Very Preterm Infants: Findings Predict Language and Cognitive Development at Two Years of Age. PLoS ONE. 8(12). e85475–e85475. 21 indexed citations

15.

Parikh, Nehal A., et al.. (2013). Automatically Quantified Diffuse Excessive High Signal Intensity on MRI Predicts Cognitive Development in Preterm Infants. Pediatric Neurology. 49(6). 424–430. 25 indexed citations

16.

He, Lili & Nehal A. Parikh. (2012). Automated detection of white matter signal abnormality using T2 relaxometry: Application to brain segmentation on term MRI in very preterm infants. NeuroImage. 64. 328–340. 19 indexed citations

17.

He, Lili, et al.. (2010). A Spatio-Temporal Deconvolution Method to Improve Perfusion CT Quantification. IEEE Transactions on Medical Imaging. 29(5). 1182–1191. 25 indexed citations

18.

He, Lili, et al.. (2009). A Nonlocal Maximum Likelihood Estimation Method for Rician Noise Reduction in MR Images. IEEE Transactions on Medical Imaging. 28(2). 165–172. 128 indexed citations

19.

Shi, Zhengang & Lili He. (2009). Text Segmentation Approach Based on Recursive Particle Filter. 4. 1–4. 1 indexed citations

20.

He, Lili, et al.. (2008). An MRF spatial fuzzy clustering method for fMRI SPMs. Biomedical Signal Processing and Control. 3(4). 327–333. 16 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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