Cargando…
Unveiling the Comorbidities of Chronic Diseases in Serbia Using ML Algorithms and Kohonen Self-Organizing Maps for Personalized Healthcare Frameworks
In previous years, significant attempts have been made to enhance computer-aided diagnosis and prediction applications. This paper presents the results obtained using different machine learning (ML) algorithms and a special type of a neural network map to uncover previously unknown comorbidities ass...
Autores principales: | Rankovic, Nevena, Rankovic, Dragica, Lukic, Igor, Savic, Nikola, Jovanovic, Verica |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10381364/ https://www.ncbi.nlm.nih.gov/pubmed/37511645 http://dx.doi.org/10.3390/jpm13071032 |
Ejemplares similares
-
Ensemble model for predicting chronic non-communicable diseases using Latin square extraction and fuzzy-artificial neural networks from 2013 to 2019
por: Rankovic, Nevena, et al.
Publicado: (2023) -
A Novel Approach of Determining the Risks for the Development of Hyperinsulinemia in the Children and Adolescent Population Using Radial Basis Function and Support Vector Machine Learning Algorithm
por: Lukić, Igor, et al.
Publicado: (2022) -
Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents
por: Lukic, Igor, et al.
Publicado: (2021) -
Innovation in Hyperinsulinemia Diagnostics with ANN-L(atin square) Models
por: Rankovic, Nevena, et al.
Publicado: (2023) -
Improved Effort and Cost Estimation Model Using Artificial Neural Networks and Taguchi Method with Different Activation Functions
por: Rankovic, Nevena, et al.
Publicado: (2021)