OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Comparison of MPL-ANN and PLS-DA models for predicting the severity of patients with acute pancreatitis: An exploratory study
Xinrui Jin, Zixuan Ding, Tao Li, et al.
The American Journal of Emergency Medicine (2021) Vol. 44, pp. 85-91
Closed Access | Times Cited: 23

Showing 23 citing articles:

Improved outcome prediction in acute pancreatitis with generated data and advanced machine learning algorithms
Murat Özdede, Ali Batur, Alp Eren Aksoy
Turkish Journal of Emergency Medicine (2025) Vol. 25, Iss. 1, pp. 32-40
Open Access

A chemometric and machine learning scheme for classification of 37 kinds of aerial parts of medicinal herbs based on ATR-FTIR
Christina Soyoung Song, Yaling An, Wenjie Zhao, et al.
Microchemical Journal (2025), pp. 112671-112671
Closed Access

Development and validation of an explainable machine learning model for mortality prediction among patients with infected pancreatic necrosis
Caihong Ning, Hui Ouyang, Jie Xiao, et al.
EClinicalMedicine (2025) Vol. 80, pp. 103074-103074
Closed Access

Machine learning predictive models for acute pancreatitis: A systematic review
You Zhou, Yutong Ge, Xiaolei Shi, et al.
International Journal of Medical Informatics (2021) Vol. 157, pp. 104641-104641
Open Access | Times Cited: 51

Improving mortality prediction in Acute Pancreatitis by machine learning and data augmentation
M Asad Bin Hameed, Zareen Alamgir
Computers in Biology and Medicine (2022) Vol. 150, pp. 106077-106077
Closed Access | Times Cited: 25

Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis
Wandong Hong, Yajing Lu, Xiaoying Zhou, et al.
Frontiers in Cellular and Infection Microbiology (2022) Vol. 12
Open Access | Times Cited: 21

Comparing Machine Learning and PLSDA Algorithms for Durian Pulp Classification Using Inline NIR Spectra
Dharma Raj Pokhrel, Panmanas Sirisomboon, Lampan Khurnpoon, et al.
Sensors (2023) Vol. 23, Iss. 11, pp. 5327-5327
Open Access | Times Cited: 12

Big Data in Gastroenterology Research
Madeline Alizadeh, Natalia Sampaio Moura, Alyssa Schledwitz, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 2458-2458
Open Access | Times Cited: 9

Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis
Rui Qian, Jiamei Zhuang, Xie Jianjun, et al.
Heliyon (2024) Vol. 10, Iss. 8, pp. e29603-e29603
Open Access | Times Cited: 2

Laser wavelength and sample conditioning effects on biochemical monitoring of SARS-CoV-2 VLP production upstream stage by Raman spectroscopy
Felipe Moura Dias, Júlia Públio Rabello, Luis Giovani Oliveira Guardalini, et al.
Biochemical Engineering Journal (2024) Vol. 211, pp. 109441-109441
Closed Access | Times Cited: 2

Prediction of the severity of acute pancreatitis using machine learning models
You Zhou, Fei Han, Xiaolei Shi, et al.
Postgraduate Medicine (2022) Vol. 134, Iss. 7, pp. 703-710
Open Access | Times Cited: 10

Machine learning-based decision tool for selecting patients with idiopathic acute pancreatitis for endosonography to exclude a biliary aetiology
Simon Sirtl, Michał Żorniak, Eric Hohmann, et al.
World Journal of Gastroenterology (2023) Vol. 29, Iss. 35, pp. 5138-5153
Open Access | Times Cited: 5

Classification method for imbalanced LiDAR point cloud based on stack autoencoder
Peng Ren, Qunli Xia
Electronic Research Archive (2023) Vol. 31, Iss. 6, pp. 3453-3470
Open Access | Times Cited: 4

Early prediction of the severe course, survival, and ICU requirements in acute pancreatitis by artificial intelligence
Ali Tüzün İnce, Gökhan Silahtaroğlu, Gülseren Seven, et al.
Pancreatology (2022) Vol. 23, Iss. 2, pp. 176-186
Closed Access | Times Cited: 5

Predicting the Need for Therapeutic Intervention and Mortality in Acute Pancreatitis: A Two-Center International Study Using Machine Learning
Na Shi, Lan Lan, Jiawei Luo, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 4, pp. 616-616
Open Access | Times Cited: 4

Artificial intelligence: Applications in critical care gastroenterology
Deven Juneja
Artificial Intelligence in Gastrointestinal Endoscopy (2024) Vol. 5, Iss. 1
Open Access

The predictive validity of serum biochemical markers in case of acute biliary pancreatitis.
Adnan Riaz, Sumera Saghir, Roomana Anwar, et al.
The Professional Medical Journal (2024) Vol. 31, Iss. 05, pp. 689-693
Open Access

A Systematic Review of Machine Learning-based Prognostic Models for Acute Pancreatitis: Towards Improving Methods and Reporting Quality
Brian Critelli, Amier Hassan, Ila Lahooti, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access

Raman laser intensity and sample clarification on biochemical monitoring over Zika-VLP upstream stages
Paulo Eduardo da Silva Cavalcante, Júlia Públio Rabello, Jaci Leme, et al.
Biochemical and Biophysical Research Communications (2024), pp. 150671-150671
Closed Access

Chemometrics and analytical blank on the at-line monitoring of Zika-VLP production using near Infrared spectroscopy
Júlia Públio Rabello, Paulo Eduardo da Silva Cavalcante, Jaci Leme, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) Vol. 326, pp. 125217-125217
Closed Access

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