Jesus Alcala-Fdez

Professor

Universidad de Granada

Spain

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Jesus Alcala-Fdez is a Professor at the University of Granada, Spain. His research focuses on areas including interpretable machine learning, fuzzy control systems, and omics data applications in pediatric obesity and cardiometabolic health. His recent work explores the use of explainable artificial intelligence for early diagnosis of insulin resistance and the relationship between gene expression and metabolic syndrome in children.

Articles (13)

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2025

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2024

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2024

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2023

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2023

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2023

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2023

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2022

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2022

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2020

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Rafael Alcalá Fernández

Universidad de Granada

SPAIN

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Eduardo Andrés-León

Head of Bioinformatics (Bioinformatics for Health Lab: B4H)

SPAIN

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Francisco Javier Ruiz Ojeda

Universidad de Granada

SPAIN

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Azahara I. Ruperez

Universidad de Granada

SPAIN

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Mercedes Gil-Campos

Professor of Pediatrics

Universidad de Córdoba

SPAIN

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Jesus Alcala-Fdez

Research Interests

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Articles (13)

Interpretable Fuzzy Control for Energy Management in Smart Buildings Using JFML-IoT and IEEE Std 1855-2016

Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: A pediatric population-based longitudinal study

Leveraging Machine Learning and Genetic Risk Scores for the Prediction of Metabolic Syndrome in Children with Obesity

Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression

Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in children with obesity

Learning positive-negative rule-based fuzzy associative classifiers with a good trade-off between complexity and accuracy

Omics Data Preprocessing for Machine Learning: A Case Study in Childhood Obesity

Transparent but Accurate Evolutionary Regression Combining New Linguistic Fuzzy Grammar and a Novel Interpretable Linear Extension

Mining high average-utility sequential rules to identify high-utility gene expression sequences in longitudinal human studies

Omics Approaches in Adipose Tissue and Skeletal Muscle Addressing the Role of Extracellular Matrix in Obesity and Metabolic Dysfunction

Evaluation of the Predictive Ability, Environmental Regulation and Pharmacogenetics Utility of a BMI-Predisposing Genetic Risk Score during Childhood and Puberty

Temporal association rule mining: An overview considering the time variable as an integral or implied component

eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research

Collaborators (10)

MARIA JESUS Alvarez Cubero

Francisco Jesus Llorente-Cantarero

Jose Manuel Soto-Hidalgo

María José Gacto

Gloria Bueno-Lozano

Rafael Alcalá Fernández

Eduardo Andrés-León

Francisco Javier Ruiz Ojeda

Azahara I. Ruperez

Mercedes Gil-Campos

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