Towards an Explainable AI-Based Tool to Predict Preterm Birth.

Kyparissidis Kokkinidis, Ilias; Logaras, Evangelos; Rigas, Emmanouil S; Tsakiridis, Ioannis; Dagklis, Themistoklis; Billis, Antonis; Bamidis, Panagiotis D

Kyparissidis Kokkinidis, Ilias; Logaras, Evangelos; Rigas, Emmanouil S; Tsakiridis, Ioannis; Dagklis, Themistoklis; Billis, Antonis; Bamidis, Panagiotis D.

Afiliación

Kyparissidis Kokkinidis I; Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece.
Logaras E; Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece.
Rigas ES; Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece.
Tsakiridis I; 3rd Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece.
Dagklis T; 3rd Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece.
Billis A; Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece.
Bamidis PD; Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece.

Stud Health Technol Inform ; 302: 571-575, 2023 May 18.

Article en En | MEDLINE | ID: mdl-37203750

Asunto(s)

Inteligencia Artificial; Nacimiento Prematuro; Recién Nacido; Embarazo; Femenino; Humanos; Nacimiento Prematuro/diagnóstico; Algoritmos; Aprendizaje Automático; Benchmarking

Palabras clave

Artificial Intelligence (AI); Clinical; Decision Support Systems; Explainable Artificial Intelligence (XAI); Machine Learning (ML); Obstetrics and Gynecology (specialty); Premature Birth

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Nacimiento Prematuro Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Newborn / Pregnancy Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article País de afiliación: Grecia Pais de publicación: Países Bajos

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