Huiling Chen
Impact in
- Artificial Intelligence top 0.01%
- Metaheuristic Optimization Algorithms Research
- AI in cancer detection
- Health Information Management top 0.1%
- Artificial Intelligence in Healthcare
Papers in
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- Metaheuristic Optimization Algorithms Research 250
- Machine Learning and ELM 9
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- Medical Image Segmentation Techniques 13
- Co-authors
- Ali Asghar Heidari (251 shared papers)Mingjing Wang (77 shared papers)Seyedali Mirjalili (3 shared papers)Majdi M. Mafarja (28 shared papers)Hossam Faris (2 shared papers)Ibrahim Aljarah (2 shared papers)Xuehua Zhao (52 shared papers)Amir H. Gandomi (5 shared papers)
In The Last Decade
Huiling Chen
713 papers receiving 41.5k citations
Huiling Chen's Hit Papers
Peers
Comparison fields: 5 of 191
- Artificial Intelligence 16.4k
- Health Information Management 898
- Renewable Energy, Sustainability and the Environment 1.9k
- Computer Vision and Pattern Recognition 1.7k
- Energy Engineering and Power Technology 93
Countries citing papers authored by Huiling Chen
This map shows the geographic impact of Huiling Chen'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 Huiling Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huiling Chen more than expected).
Fields of papers citing papers by Huiling Chen
This network shows the impact of papers produced by Huiling Chen. 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 Huiling Chen. The network helps show where Huiling Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Huiling Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 766 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Harris hawks optimization: Algorithm and applications Hit paper breakdown → | 2019 | 5043 |
| 2 | Slime mould algorithm: A new method for stochastic optimization Hit paper breakdown → | 2020 | 2502 |
| 3 | RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method Hit paper breakdown → | 2021 | 937 |
| 4 | Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts Hit paper breakdown → | 2021 | 923 |
| 5 | RIME: A physics-based optimization Hit paper breakdown → | 2023 | 752 |
| 6 | INFO: An efficient optimization algorithm based on weighted mean of vectors Hit paper breakdown → | 2022 | 681 |
| 7 | The Colony Predation Algorithm Hit paper breakdown → | 2021 | 516 |
| 8 | Evolving support vector machines using fruit fly optimization for medical data classification Hit paper breakdown → | 2016 | 473 |
| 9 | Toward an optimal kernel extreme learning machine using a chaotic moth-flame optimization strategy with applications in medical diagnoses Hit paper breakdown → | 2017 | 406 |
| 10 | Chaotic multi-swarm whale optimizer boosted support vector machine for medical diagnosis Hit paper breakdown → | 2019 | 386 |
| 11 | An enhanced fast non-dominated solution sorting genetic algorithm for multi-objective problems Hit paper breakdown → | 2021 | 377 |
| 12 | Enhanced Moth-flame optimizer with mutation strategy for global optimization Hit paper breakdown → | 2019 | 373 |
| 13 | A support vector machine classifier with rough set-based feature selection for breast cancer diagnosis Hit paper breakdown → | 2011 | 321 |
| 14 | A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique Hit paper breakdown → | 2021 | 315 |
| 15 | Generative Adversarial Networks in Medical Image augmentation: A review Hit paper breakdown → | 2022 | 308 |
| 16 | Parrot optimizer: Algorithm and applications to medical problems Hit paper breakdown → | 2024 | 301 |
| 17 | 2019 | 287 | |
| 18 | 2020 | 284 | |
| 19 | 2020 | 282 | |
| 20 | Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients Hit paper breakdown → | 2018 | 279 |
About Huiling Chen
Huiling Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Renewable Energy, Sustainability and the Environment, Information Systems and Health Information Management, having authored 766 papers that have together received 42.4k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (250 papers), Photovoltaic System Optimization Techniques (23 papers), Medical Image Segmentation Techniques (13 papers), Artificial Intelligence in Healthcare (11 papers), Blockchain Technology Applications and Security (11 papers), Advanced Multi-Objective Optimization Algorithms (9 papers), Machine Learning and ELM (9 papers) and Neural Networks Stability and Synchronization (7 papers). The work is most often cited by research in Artificial Intelligence (16.4k citations), Health Information Management (898 citations), Renewable Energy, Sustainability and the Environment (1.9k citations), Computer Vision and Pattern Recognition (1.7k citations) and Energy Engineering and Power Technology (93 citations). Huiling Chen has collaborated with scholars based in China, Iran and Singapore. Frequent co-authors include Ali Asghar Heidari, Mingjing Wang, Seyedali Mirjalili, Majdi M. Mafarja, Hossam Faris, Ibrahim Aljarah, Xuehua Zhao, Amir H. Gandomi, Zhennao Cai and Chengye Li. Their work appears in journals such as Expert Systems with Applications, IEEE Access, Biomedical Signal Processing and Control, Computers in Biology and Medicine and Journal of Computational Design and Engineering.
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.