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An explainable XGBoost-based approach towards assessing the risk of
  cardiovascular disease in patients with Type 2 Diabetes Mellitus
v1v2 (latest)

An explainable XGBoost-based approach towards assessing the risk of cardiovascular disease in patients with Type 2 Diabetes Mellitus

14 September 2020
M. Athanasiou
Konstantina Sfrintzeri
K. Zarkogianni
Anastasia C. Thanopoulou
K. Nikita
ArXiv (abs)PDFHTML

Papers citing "An explainable XGBoost-based approach towards assessing the risk of cardiovascular disease in patients with Type 2 Diabetes Mellitus"

5 / 5 papers shown
Title
Sustaining model performance for covid-19 detection from dynamic audio
  data: Development and evaluation of a comprehensive drift-adaptive framework
Sustaining model performance for covid-19 detection from dynamic audio data: Development and evaluation of a comprehensive drift-adaptive framework
Theofanis Ganitidis
M. Athanasiou
Konstantinos Mitsis
K. Zarkogianni
Konstantina S. Nikita
91
0
0
28 Sep 2024
Explainable LightGBM Approach for Predicting Myocardial Infarction
  Mortality
Explainable LightGBM Approach for Predicting Myocardial Infarction Mortality
Ana Letícia Garcez Vicente
Roseval Malaquias Junior
R. Romero
38
2
0
23 Apr 2024
Cross-lingual Dysarthria Severity Classification for English, Korean,
  and Tamil
Cross-lingual Dysarthria Severity Classification for English, Korean, and Tamil
Eunjung Yeo
Kwanghee Choi
Sunhee Kim
Minhwa Chung
51
8
0
26 Sep 2022
Machine Learning Method for Functional Assessment of Retinal Models
Machine Learning Method for Functional Assessment of Retinal Models
N. Papadopoulos
Nikos Melanitis
Antonio Lozano
C. Soto-Sánchez
E. Fernández
K. Nikita
19
5
0
05 Feb 2022
Interpretability methods of machine learning algorithms with
  applications in breast cancer diagnosis
Interpretability methods of machine learning algorithms with applications in breast cancer diagnosis
P. Karatza
K. Dalakleidi
M. Athanasiou
K. Nikita
26
17
0
04 Feb 2022
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