Ling Ma

860 citations
45 papers · 528 indexed · 1 hit paper · h-index 11

Impact in

  • Accounting top 5%
    • Financial Distress and Bankruptcy Prediction
    • Auditing, Earnings Management, Governance
  • Finance top 10%
    • Credit Risk and Financial Regulations

Papers in

Ling Ma

42 papers receiving 512 citations

Hit Papers

Deep learning models for bankruptcy prediction using textual disclosures 2018 · 272 citations
272201820262020202350100150200250

Peers

Ling Ma
Comparison fields: 5 of 101
  • Accounting 199
  • Finance 80
  • Otorhinolaryngology 28
  • Management Science and Operations Research 75
  • Media Technology 44
Replace Lin Ma with:
Lin Ma United States
Zuherman Rustam Indonesia
Rashmi Malhotra United States
Mehdi Shajari Germany
Chongqing Liu China
Αναστάσιος Πετρόπουλος Greece
Ni He China
Yu Xie China
Ling Ma relative to Lin Ma United States Lin Ma's profile →
Citations per field
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Lin Ma · 1×
Citations per year

Countries citing papers authored by Ling Ma

Since Specialization
Citations

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

Fields of papers citing papers by Ling Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Ling Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ling Ma Line = papers co-authored together Ling Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20240
3 202410
4 20242
5 20231
6 202214
7 20225
8 20222
9 202137
10 20218
11 202016
12 20201
13 20191
14 20184
15 20185
16
Deep learning models for bankruptcy prediction using textual disclosures
Hit paper breakdown →
2018272
17 20166
18
The effect of intensity-modulated radiotherapy versus conventional radiotherapy on quality of life in patients with nasopharyngeal cancer: a cross-sectional study.
20135
19 20131
20 20113

About Ling Ma

Ling Ma is a scholar working on Otorhinolaryngology, Computer Vision and Pattern Recognition, Media Technology, Industrial and Manufacturing Engineering and Radiology, Nuclear Medicine and Imaging, having authored 45 papers that have together received 528 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (9 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), COVID-19 diagnosis using AI (6 papers), Industrial Vision Systems and Defect Detection (6 papers), Advanced Image Fusion Techniques (4 papers), Multiple Myeloma Research and Treatments (4 papers), AI in cancer detection (4 papers) and Surface Roughness and Optical Measurements (3 papers). The work is most often cited by research in Accounting (199 citations), Finance (80 citations), Otorhinolaryngology (28 citations), Management Science and Operations Research (75 citations) and Media Technology (44 citations). Ling Ma has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Feng Mai, Shaonan Tian, Chihoon Lee, Huiqin Jiang, Lihua Jian, Rakiba Rayhana, Zheng Liu, Yueqi Sun, Jianbo Shi and Rui Xu. Their work appears in journals such as IEEE Access, BMJ Open, Advances in experimental medicine and biology, IEEE Journal of Biomedical and Health Informatics and PeerJ Computer Science.

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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