Liting Shi

1.4k total citations · 1 hit paper
63 papers, 970 citations indexed

About

Liting Shi is a scholar working on Mechanical Engineering, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Liting Shi has authored 63 papers receiving a total of 970 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Mechanical Engineering, 25 papers in Radiology, Nuclear Medicine and Imaging and 11 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Liting Shi's work include Radiomics and Machine Learning in Medical Imaging (19 papers), Advanced Welding Techniques Analysis (18 papers) and Aluminum Alloys Composites Properties (14 papers). Liting Shi is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (19 papers), Advanced Welding Techniques Analysis (18 papers) and Aluminum Alloys Composites Properties (14 papers). Liting Shi collaborates with scholars based in China, United States and Canada. Liting Shi's co-authors include Jianfeng Qiu, Jidong Kang, Blair E. Carlson, Amberlee S. Haselhuhn, Yi Rong, David R. Sigler, Babak Shalchi Amirkhiz, Stanley Benedict, Yihui Wei and Jichuan Kong and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Materials Science and Engineering A and Frontiers in Immunology.

In The Last Decade

Liting Shi

56 papers receiving 953 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Carbon Quantum Dots: Properties, Preparation, and Applications

2024 104 citations Liting Shi et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Liting Shi China	19	335	300	163	156	147	63	970
Hidetoshi KOBAYASHI Japan	16	628 1.9×	39 0.1×	303 1.9×	80 0.5×	102 0.7×	152	1.3k
Anuradha Godavarty United States	18	82 0.2×	877 2.9×	84 0.5×	950 6.1×	15 0.1×	99	1.3k
Zhongshuai Zhang China	16	38 0.1×	213 0.7×	32 0.2×	59 0.4×	86 0.6×	63	744
Nikolaos Vlachos Greece	16	202 0.6×	44 0.1×	240 1.5×	169 1.1×	32 0.2×	36	739
Dapeng Shi China	21	75 0.2×	645 2.1×	63 0.4×	48 0.3×	6 0.0×	56	1.3k
M. Bauer Germany	16	58 0.2×	410 1.4×	60 0.4×	94 0.6×	6 0.0×	38	901
Guangfeng Zhang China	15	32 0.1×	47 0.2×	91 0.6×	50 0.3×	27 0.2×	84	1.1k
J. Liu China	19	72 0.2×	216 0.7×	251 1.5×	121 0.8×	39 0.3×	58	939
Mark E. Schafer United States	20	46 0.1×	394 1.3×	40 0.2×	494 3.2×	20 0.1×	67	1.1k

Countries citing papers authored by Liting Shi

Since Specialization

Citations

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

Fields of papers citing papers by Liting Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liting Shi

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

Shi, Liting, Jiayi Zhang, Jianlin Wang, et al.. (2025). Transformer-based structural connectivity networks for ADHD-related connectivity alterations. Communications Medicine. 5(1). 296–296. 1 indexed citations

Feng, Siyang, Liting Shi, Zhenbing Liu, et al.. (2025). Wave-aware Weakly Supervised Histopathological Tissue Segmentation with Cross-scale Logits Distillation. IEEE Transactions on Medical Imaging. PP. 1–1.

Qi, Yana, et al.. (2025). A preoperative predictive model based on multi-modal features to predict pathological complete response after neoadjuvant chemoimmunotherapy in esophageal cancer patients. Frontiers in Immunology. 16. 1530279–1530279. 2 indexed citations

Shi, Liting, et al.. (2025). Role of weld nugget size at Al/steel and steel/steel interface in fatigue behavior of three-sheet Al-steel-steel dissimilar resistance spot welds. Engineering Failure Analysis. 175. 109589–109589. 2 indexed citations

Shi, Yandong, et al.. (2025). Effect of overlap scanning strategies on micro-characteristics and mechanical properties of dual-laser selective laser melted AlSi10Mg. Materials Today Communications. 49. 113730–113730.

Shi, Liting, et al.. (2025). Strengthening Mechanism of Aluminum Weld Nugget in Novel Dissimilar Resistance Spot Welds of AA5754 to Steels. Journal of Materials Engineering and Performance. 34(20). 24014–24025.

Cai, Lin, Lei Cui, Chao Huang, et al.. (2025). Association between age and lung cancer risk: evidence from lung lobar radiomics. BMC Medical Imaging. 25(1). 204–204. 1 indexed citations

Liu, Cai‐Ming, Weiqiu Chen, Liting Shi, et al.. (2024). Uniaxial and multiaxial cyclic deformation behavior prediction of Z2CN18.10 austenitic stainless steel based on Transformer deep learning method. International Journal of Fatigue. 186. 108389–108389. 3 indexed citations

Chen, Yu, et al.. (2024). Classification and prediction of chemoradiotherapy response and survival from esophageal carcinoma histopathology images. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 312. 124030–124030. 5 indexed citations

10.

Qian, Cheng, Hassan Ghassemi-Armaki, Liting Shi, et al.. (2023). Competing fracture modes in Al-steel resistance spot welded structures: Experimental evaluation and numerical prediction. International Journal of Impact Engineering. 185. 104838–104838. 11 indexed citations

11.

Liu, Cai‐Ming, et al.. (2023). Ratcheting-fatigue behavior and life prediction of Z2CN18.10 austenitic stainless steel elbow. International Journal of Pressure Vessels and Piping. 204. 104985–104985. 4 indexed citations

12.

Shi, Yandong, Cheng Luo, Wenkai Li, et al.. (2023). Fatigue properties of resistance spot‐welded maraging steel produced by selective laser melting. Fatigue & Fracture of Engineering Materials & Structures. 46(7). 2458–2472. 2 indexed citations

13.

Li, Chao, Yu Chen, Yongmei Hu, et al.. (2023). CT-based radiomics for predicting radio-chemotherapy response and overall survival in nonsurgical esophageal carcinoma. Frontiers in Oncology. 13. 1219106–1219106. 1 indexed citations

14.

Shi, Liting, Lin Shen, Junming Jian, et al.. (2023). Contribution of whole slide imaging‐based deep learning in the assessment of intraoperative and postoperative sections in neuropathology. Brain Pathology. 33(4). e13160–e13160. 7 indexed citations

15.

Shi, Liting, et al.. (2022). Multi-phase contrast-enhanced magnetic resonance image-based radiomics-combined machine learning reveals microscopic ultra-early hepatocellular carcinoma lesions. European Journal of Nuclear Medicine and Molecular Imaging. 49(8). 2917–2928. 19 indexed citations

16.

Zhang, Li, et al.. (2022). Ultrasound Image–Based Deep Features and Radiomics for the Discrimination of Small Fat-Poor Angiomyolipoma and Small Renal Cell Carcinoma. Ultrasound in Medicine & Biology. 49(2). 560–568. 7 indexed citations

17.

Shi, Liting, et al.. (2021). Surface values, volumetric measurements and radiomics of structural MRI for the diagnosis and subtyping of attention‐deficit/hyperactivity disorder. European Journal of Neuroscience. 54(10). 7654–7667. 12 indexed citations

18.

Rong, Yi, Minsong Cao, Liting Shi, et al.. (2021). A Comparison of the Distortion in the Same Field MRI and MR-Linac System With a 3D Printed Phantom. Frontiers in Oncology. 11. 579451–579451. 4 indexed citations

19.

Lu, Weizhao, et al.. (2020). Classification Of TI-RADS Class-4 Thyroid Nodules Via Ultrasound-Based Radiomics And Multi-Kernel Learning. International Journal of Radiation Oncology*Biology*Physics. 108(3). e848–e848. 1 indexed citations

20.

Zheng, Fenglian, Dong Cui, Li Zhang, et al.. (2018). The Volume of Hippocampal Subfields in Relation to Decline of Memory Recall Across the Adult Lifespan. Frontiers in Aging Neuroscience. 10. 320–320. 76 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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