Jose Luis Castillo Sequera

Full Professor

Universidad de Alcalá

Spain

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Jose Luis Castillo Sequera is a Full Professor at Universidad de Alcalá de Henares in Spain. His research primarily focuses on the application of machine learning in various domains, including health informatics, telecommunications, and environmental studies. Recent articles include topics such as sedentary lifestyle applications for home office workers and the use of blockchain for electronic health record interoperability. His work also explores advanced methodologies in predictive analytics related to vehicle accident risks and healthcare management.

Jose Luis Castillo Sequera

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Articles (22)

Sedentary: A Healthy Lifestyle App for Home Office Workers

A Systematic Review About the Use of Machine Learning Related to Earthquake Studies

Efficient Machine Learning Models for Solar Radiation Prediction Using Ensemble Techniques: A Case Study in Low-Rainfall Arid Climates

Factors, Prediction, and Explainability of Vehicle Accident Risk Due to Driving Behavior through Machine Learning: A Systematic Literature Review, 2013–2023

Electronic Health Record Interoperability System in Peru Using Blockchain

Factors, Predictability, and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature

Interoperability Blockchain, InterPlanetary File System and Health Level 7 Framework for Electronic Health Records

Intelligent System Based on Round Robin and Genetic Algorithm for Managing Nurse Schedules in Health Centres in Peru

IoT-Based Technology Solution for Monitoring Small Breed Cardiac Dogs with Heart Disease

A Learning Health-Care System for Improving Renal Health Services in Peru Using Data Analytics

Identification of trends to anticipate emergency services. : Method for hospitals popular emergency trends search

Methodical Design: Intelligent System for Vehicle Congestion Using Micro-Controllers, Programmed Hardware and Patterns

Prediction of hourly solar radiation using an Artificial Neural Network model in a district of Peru

Medical Prognosis of Infectious Diseases in Nursing Homes by Applying Machine Learning on Clinical Data Collected in Cloud Microservices

Developing a Long Short-Term Memory-Based Model for Forecasting the Daily Energy Consumption of Heating, Ventilation, and Air Conditioning Systems in Buildings

Towards a Service-Oriented Architecture for the Energy Efficiency of Buildings: A Systematic Review

Detection of phytophthora palmivora in cocoa fruit with deep learning

Machine Learning Applied to Diagnosis of Human Diseases: A Systematic Review

Study to Determine Levels of Cadmium in Cocoa Crops Applied to Inland Areas of Peru: “The Case of the Campo Verde-Honoria Tournavista Corridor”

Water Treatment Plant Prototype with pH Control Modeled on Fuzzy Logic for Removing Arsenic Using Fe(VI) and Fe(III)

Design of a Predictive Model of Rock Breakage by Blasting Using Artificial Neural Networks

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

Collaborators (4)

Alberto Garces

Nuria C. Caballé

Juan A. Gómez-Pulido

JOSÉ MANUEL GÓMEZ PULIDO

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