KJIM :: Korean Journal of Internal Medicine

Diabetes management, dietary supplements use and the effect of coronavirus pandemic on diabetes patients in Serbia: a cross-sectional study

Milana Vuković, Jelena Jovičić Bata, Nemanja Todorović, Gorana Puača, Dunja Vesković, Jelena Čanji Panić, Tihomir Dugandžija, Mladena Lalić-Popović

Current Medical Research and Opinion.2024; 40(2): 165. CrossRef

Global Impacts of Western Diet and Its Effects on Metabolism and Health: A Narrative Review

Vicente Javier Clemente-Suárez, Ana Isabel Beltrán-Velasco, Laura Redondo-Flórez, Alexandra Martín-Rodríguez, José Francisco Tornero-Aguilera

Prescription pattern analysis of Type 2 Diabetes Mellitus: a cross-sectional study in Isfahan, Iran

Elnaz Ziad, Somayeh Sadat, Farshad Farzadfar, Mohammad-Reza Malekpour

A Machine Learning Approach for Identification of Malignant Mesothelioma Etiological Factors in an Imbalanced Dataset

Talha Mahboob Alam, Kamran Shaukat, Haris Mahboob, Muhammad Umer Sarwar, Farhat Iqbal, Adeel Nasir, Ibrahim A Hameed, Suhuai Luo

The Computer Journal.2022; 65(7): 1740. CrossRef

Variations in comorbidity burden in people with type 2 diabetes over disease duration: A population-based analysis of real world evidence

Jonathan Pearson-Stuttard, Sara Holloway, Rosie Polya, Rebecca Sloan, Linxuan Zhang, Edward W. Gregg, Katy Harrison, Jamie Elvidge, Pall Jonsson, Thomas Porter

eClinicalMedicine.2022; 52: 101584. CrossRef

Detection and Prediction of Diabetes Using Data Mining: A Comprehensive Review

Farrukh Aslam Khan, Khan Zeb, Mabrook Al-Rakhami, Abdelouahid Derhab, Syed Ahmad Chan Bukhari

MorbiNet: multimorbidity networks in adult general population. Analysis of type 2 diabetes mellitus comorbidity

Alba Aguado, Ferran Moratalla-Navarro, Flora López-Simarro, Victor Moreno

Inferring Relationship of Blood Metabolic Changes and Average Daily Gain With Feed Conversion Efficiency in Murrah Heifers: Machine Learning Approach

Poonam Sikka, Abhigyan Nath, Shyam Sundar Paul, Jerome Andonissamy, Dwijesh Chandra Mishra, Atmakuri Ramakrishna Rao, Ashok Kumar Balhara, Krishna Kumar Chaturvedi, Keerti Kumar Yadav, Sunesh Balhara

Frontiers in Veterinary Science.2020;[Epub] CrossRef

Using association rule mining to jointly detect clinical features and differentially expressed genes related to chronic inflammatory diseases

Rosana Veroneze, Sâmia Cruz Tfaile Corbi, Bárbara Roque da Silva, Cristiane de S. Rocha, Cláudia V. Maurer-Morelli, Silvana Regina Perez Orrico, Joni A. Cirelli, Fernando J. Von Zuben, Raquel Mantuaneli Scarel-Caminaga, Paolo Magni

Comorbidity Patterns of Older Lung Cancer Patients in Northeast China: An Association Rules Analysis Based on Electronic Medical Records

International Journal of Environmental Research and Public Health.2020; 17(23): 9119. CrossRef

Examining Development Processes for Text Messaging Interventions to Prevent Cardiovascular Disease: Systematic Literature Review

Ignacio Ricci-Cabello, Kirsten Bobrow, Sheikh Mohammed Shariful Islam, Clara K Chow, Ralph Maddison, Robyn Whittaker, Andrew J Farmer

JMIR mHealth and uHealth.2019; 7(3): e12191. CrossRef

Mental disorders and medical comorbidities: Association rule mining approach

Chia-Hui Wang, Tzu-Yin Lee, King-Cheung Hui, Min-Huey Chung

Perspectives in Psychiatric Care.2019; 55(3): 517. CrossRef

Type 2 diabetes mellitus and multiple chronic diseases

Nailya S. Asfandiyarova, Olga V. Dashkevich, Natalya V. Doroshina, Ekaterina I. Suchkova

Diabetes mellitus.2019; 21(6): 455. CrossRef

Development of a new metric to identify rare patterns in association analysis: The case of analyzing diabetes complications

Saeed Piri, Dursun Delen, Tieming Liu, William Paiva

Expert Systems with Applications.2018; 94: 112. CrossRef

Anesthesia in children with comorbid pathology - clinical assessment of the most common pathological conditions in the practice of anesthesiologist

Effects of dipeptidyl peptidase-4 inhibitors on blood pressure in patients with type 2 diabetes

Journal of Hypertension.2016; 34(2): 167. CrossRef

An Application of Association Rule Mining to Extract Risk Pattern for Type 2 Diabetes Using Tehran Lipid and Glucose Study Database

Azra Ramezankhani, Omid Pournik, Jamal Shahrabi, Fereidoun Azizi, Farzad Hadaegh

International Journal of Endocrinology and Metabolism.2015;[Epub] CrossRef

Predicting Metabolic Syndrome Using the Random Forest Method

Apilak Worachartcheewan, Watshara Shoombuatong, Phannee Pidetcha, Wuttichai Nopnithipat, Virapong Prachayasittikul, Chanin Nantasenamat

The Scientific World Journal.2015; 2015: 1. CrossRef

Extending Association Rule Summarization Techniques to Assess Risk of Diabetes Mellitus

György J. Simon, Pedro J. Caraballo, Terry M. Therneau, Steven S. Cha, M. Regina Castro, Peter W. Li

IEEE Transactions on Knowledge and Data Engineering.2015; 27(1): 130. CrossRef

Prevalence and comorbidities of known diabetes in northeastern Italy

Francesca Valent, Silvia Tillati, Loris Zanier

Journal of Diabetes Investigation.2013; 4(4): 355. CrossRef