Lazaros Tzelves

According to our database1, Lazaros Tzelves authored at least 12 papers between 2021 and 2024.

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Bibliography

2024
Evaluating the interactions of Medical Doctors with chatbots based on large language models: Insights from a nationwide study in the Greek healthcare sector using ChatGPT.
Comput. Hum. Behav., 2024

Evaluating ChatGPT 4.0's User Satisfaction Among Doctors Across Different Medical Departments.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

2023
Acceptance of Artificial Intelligence in Supporting Cancer Patients.
Proceedings of the Healthcare Transformation with Informatics and Artificial Intelligence, 2023

Training ChatGPT Models in Assisting Urologists in Daily Practice.
Proceedings of the Healthcare Transformation with Informatics and Artificial Intelligence, 2023

2022
Prediction of Hospitalization Using Machine Learning for Emergency Department Patients.
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Cluster Analysis Assessment in Proposing a Surgical Technique for Benign Prostatic Enlargement.
Proceedings of the Advances in Informatics, Management and Technology in Healthcare, 2022

Using Association Rules in Antimicrobial Resistance in Stone Disease Patients.
Proceedings of the Advances in Informatics, Management and Technology in Healthcare, 2022

Exploratory Clustering for Emergency Department Patients.
Proceedings of the Advances in Informatics, Management and Technology in Healthcare, 2022

Using Machine Learning for Predicting the Hospitalization of Emergency Department Patients.
Proceedings of the Advances in Informatics, Management and Technology in Healthcare, 2022

2021
Using machine learning techniques to predict hospital admission at the emergency department.
CoRR, 2021

Admission and Discharge Following Ambulance Transport to the Emergency Department.
Proceedings of the Informatics and Technology in Clinical Care and Public Health, 2021

Predicting Hospital Admission for Emergency Department Patients: A Machine Learning Approach.
Proceedings of the Informatics and Technology in Clinical Care and Public Health, 2021


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