Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Showing 12 citing articles:

Transparent machine learning suggests a key driver in the decision to start insulin therapy in individuals with type 2 diabetes
Nicoletta Musacchio, Rita Zilich, Paola Ponzani, et al.
Journal of Diabetes (2023) Vol. 15, Iss. 3, pp. 224-236
Open Access | Times Cited: 31
Phenotyping obesity: A focus on metabolically healthy obesity and metabolically unhealthy normal weight
Rachel Agius, Nikolai Paul Pace, Stephen Fava
Diabetes/Metabolism Research and Reviews (2023) Vol. 40, Iss. 2
Open Access | Times Cited: 18
Rethinking weight loss treatments as cardiovascular medicine in obesity, a comprehensive review
Dario Tuccinardi, Mikiko Watanabe, Davide Masi, et al.
European Journal of Preventive Cardiology (2024) Vol. 31, Iss. 10, pp. 1260-1273
Closed Access | Times Cited: 4
Predictors of weight loss in patients with obesity treated with a Very Low-Calorie Ketogenic Diet
Ilaria Ernesti, Francesco Baratta, Mikiko Watanabe, et al.
Frontiers in Nutrition (2023) Vol. 10
Open Access | Times Cited: 9
Differences in the levels of inflammatory markers between metabolically healthy obese and other obesity phenotypes in adults: A systematic review and meta-analysis
Z Su, Ljupcho Efremov, Rafael Mikolajczyk
Nutrition Metabolism and Cardiovascular Diseases (2023) Vol. 34, Iss. 2, pp. 251-269
Closed Access | Times Cited: 7
Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group
Davide Masi, Rita Zilich, Riccardo Candido, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 12, pp. 4095-4095
Open Access | Times Cited: 6
Obesity-Associated Hepatic Steatosis, Somatotropic Axis Impairment, and Ferritin Levels Are Strong Predictors of COVID-19 Severity
Davide Masi, Elena Gangitano, Anna Criniti, et al.
Viruses (2023) Vol. 15, Iss. 2, pp. 488-488
Open Access | Times Cited: 4
Exploring the State of Machine Learning and Deep Learning in Medicine: A Survey of Italian Research Community
Alessio Bottrighi, Marzio Pennisi
(2023)
Open Access | Times Cited: 3
Exploring the State of Machine Learning and Deep Learning in Medicine: A Survey of the Italian Research Community
Alessio Bottrighi, Marzio Pennisi
Information (2023) Vol. 14, Iss. 9, pp. 513-513
Open Access | Times Cited: 3
Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases
J. Alfredo Martínéz, Marta Alonso-Bernáldez, Diego Martínez‐Urbistondo, et al.
World Journal of Gastroenterology (2022) Vol. 28, Iss. 44, pp. 6230-6248
Open Access | Times Cited: 4
La medicina cardiometabolica nell’obesità

il Diabete (2024) Vol. 35, Iss. 4
Open Access
A transparent machine learning algorithm uncovers HbA1c patterns associated with therapeutic inertia in patients with type 2 diabetes and failure of metformin monotherapy
Nicoletta Musacchio, Rita Zilich, Davide Masi, et al.
International Journal of Medical Informatics (2024) Vol. 190, pp. 105550-105550
Open Access
Page 1

Scroll to top