New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography

doi:doi:10.57702/1vzg95x7

New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography

The dataset used in this study is a large outpatient cohort of patients who underwent electrocardiogram (ECG) and hemoglobin A1c (HbA1c) testing. The dataset contains information on patient demographics, medical history, and ECG and HbA1c results.

BibTex:

@dataset{Neil_Jethania_and_Aahlad_Pulib_and_Hao_Zhanga_and_Leonid_Garbera_and_Lior_Jankelsona_and_Yindalon_Aphinyanaphongsa_and_Rajesh_Ranganatha_2024,
    abstract = {The dataset used in this study is a large outpatient cohort of patients who underwent electrocardiogram (ECG) and hemoglobin A1c (HbA1c) testing. The dataset contains information on patient demographics, medical history, and ECG and HbA1c results.},
    author = {Neil Jethania and Aahlad Pulib and Hao Zhanga and Leonid Garbera and Lior Jankelsona and Yindalon Aphinyanaphongsa and Rajesh Ranganatha},
    doi = {10.57702/1vzg95x7},
    institution = {No Organization},
    keyword = {'artificial intelligence', 'diabetes', 'electrocardiogram', 'hemoglobin A1c'},
    month = {dec},
    publisher = {TIB},
    title = {New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography},
    url = {https://service.tib.eu/ldmservice/dataset/new-onset-diabetes-assessment-using-artificial-intelligence-enhanced-electrocardiography},
    year = {2024}
}