Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease. Gut microbiota plays a key role in metabolic homeostasis and the development of T2DM and its complications. With the advance of artificial intelligence (AI), it is possible to develop novel models based on machine learning (ML) that can...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/4/2228 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849719074236399616 |
|---|---|
| author | Pablo Caballero-María Javier Caballero-Villarraso Javier Arenas-Montes Alberto Díaz-Cáceres Sofía Castañeda-Nieto Juan F. Alcalá-Díaz Javier Delgado-Lista Fernando Rodríguez-Cantalejo Pablo Pérez-Martínez José López-Miranda Antonio Camargo |
| author_facet | Pablo Caballero-María Javier Caballero-Villarraso Javier Arenas-Montes Alberto Díaz-Cáceres Sofía Castañeda-Nieto Juan F. Alcalá-Díaz Javier Delgado-Lista Fernando Rodríguez-Cantalejo Pablo Pérez-Martínez José López-Miranda Antonio Camargo |
| author_sort | Pablo Caballero-María |
| collection | DOAJ |
| description | Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease. Gut microbiota plays a key role in metabolic homeostasis and the development of T2DM and its complications. With the advance of artificial intelligence (AI), it is possible to develop novel models based on machine learning (ML) that can predict the risk of developing certain diseases and facilitate their early diagnosis, or even take preventive measures in advance. This can be the case of T2DM, for example. Our objective was to develop a predictive model of the risk of developing T2DM based on clinical, biochemical, and intestinal microbiota parameters, which estimates the time margin for developing this disease. To this end, a Deep Learning Multilayer Perceptron (MLP) algorithm was developed and trained with data from real patients from a current large population epidemiological study. The data were normalised and augmented to increase their diversity and avoid overfitting. The neural network developed was optimised, and the best hyperparameters were chosen for model building by Bayesian optimisation. We succeeded in getting the model to return a numerical result corresponding to the number of months it will take for a particular individual to develop T2DM with an accuracy of 95.2%. |
| format | Article |
| id | doaj-art-c126ba6cbc6244529d2b2d7254fe351c |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-c126ba6cbc6244529d2b2d7254fe351c2025-08-20T03:12:12ZengMDPI AGApplied Sciences2076-34172025-02-01154222810.3390/app15042228Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota ProfilesPablo Caballero-María0Javier Caballero-Villarraso1Javier Arenas-Montes2Alberto Díaz-Cáceres3Sofía Castañeda-Nieto4Juan F. Alcalá-Díaz5Javier Delgado-Lista6Fernando Rodríguez-Cantalejo7Pablo Pérez-Martínez8José López-Miranda9Antonio Camargo10Maimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainClinical Analyses Service, Reina Sofía University Hospital, 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainMaimónides Biomedical Research Institute of Córdoba (IMIBIC), 14004 Córdoba, SpainType 2 diabetes mellitus (T2DM) is a chronic metabolic disease. Gut microbiota plays a key role in metabolic homeostasis and the development of T2DM and its complications. With the advance of artificial intelligence (AI), it is possible to develop novel models based on machine learning (ML) that can predict the risk of developing certain diseases and facilitate their early diagnosis, or even take preventive measures in advance. This can be the case of T2DM, for example. Our objective was to develop a predictive model of the risk of developing T2DM based on clinical, biochemical, and intestinal microbiota parameters, which estimates the time margin for developing this disease. To this end, a Deep Learning Multilayer Perceptron (MLP) algorithm was developed and trained with data from real patients from a current large population epidemiological study. The data were normalised and augmented to increase their diversity and avoid overfitting. The neural network developed was optimised, and the best hyperparameters were chosen for model building by Bayesian optimisation. We succeeded in getting the model to return a numerical result corresponding to the number of months it will take for a particular individual to develop T2DM with an accuracy of 95.2%.https://www.mdpi.com/2076-3417/15/4/2228deep learningneural networkmachine learningartificial intelligencepredictive modellingdiabetes mellitus |
| spellingShingle | Pablo Caballero-María Javier Caballero-Villarraso Javier Arenas-Montes Alberto Díaz-Cáceres Sofía Castañeda-Nieto Juan F. Alcalá-Díaz Javier Delgado-Lista Fernando Rodríguez-Cantalejo Pablo Pérez-Martínez José López-Miranda Antonio Camargo Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles Applied Sciences deep learning neural network machine learning artificial intelligence predictive modelling diabetes mellitus |
| title | Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles |
| title_full | Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles |
| title_fullStr | Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles |
| title_full_unstemmed | Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles |
| title_short | Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles |
| title_sort | deep learning model approach to predict diabetes type 2 based on clinical biochemical and gut microbiota profiles |
| topic | deep learning neural network machine learning artificial intelligence predictive modelling diabetes mellitus |
| url | https://www.mdpi.com/2076-3417/15/4/2228 |
| work_keys_str_mv | AT pablocaballeromaria deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT javiercaballerovillarraso deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT javierarenasmontes deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT albertodiazcaceres deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT sofiacastanedanieto deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT juanfalcaladiaz deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT javierdelgadolista deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT fernandorodriguezcantalejo deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT pabloperezmartinez deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT joselopezmiranda deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles AT antoniocamargo deeplearningmodelapproachtopredictdiabetestype2basedonclinicalbiochemicalandgutmicrobiotaprofiles |