title: An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment.
abstract: The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).
authors.affiliation: Departamento de Química, Escola de Ciências e Tecnologia, Universidade de Évora, 7000-671, Évora, Portugal.
authors.forename: João
authors.initials: J
authors.lastname: Vilhena
authors.affiliation: Departamento de Química, Laboratório HERCULES, Escola de Ciências e Tecnologia, Universidade de Évora, 7000-671, Évora, Portugal.
authors.forename: M
authors.initials: M
authors.lastname: Rosário Martins
authors.affiliation: Departamento de Química, Escola de Ciências e Tecnologia, Universidade de Évora, 7000-671, Évora, Portugal.|Centro Algoritmi, Universidade do Minho, 4710-057, Braga, Portugal.
authors.forename: Henrique
authors.identifier: http://orcid.org/0000-0001-8456-7773
authors.initials: H
authors.lastname: Vicente
authors.affiliation: Serviço de Patologia Clínica do Hospital do Espírito Santo de Évora EPE, Évora, Portugal.
authors.forename: José M
authors.initials: JM
authors.lastname: Grañeda
authors.affiliation: Serviço de Patologia Clínica do Hospital do Espírito Santo de Évora EPE, Évora, Portugal.
authors.forename: Filomena
authors.initials: F
authors.lastname: Caldeira
authors.affiliation: Serviço de Patologia Clínica do Hospital do Espírito Santo de Évora EPE, Évora, Portugal.
authors.forename: Rodrigo
authors.initials: R
authors.lastname: Gusmão
authors.affiliation: Drs. Nicolas & Asp, Dubai, United Arab Emirates.
authors.forename: João
authors.initials: J
authors.lastname: Neves
authors.affiliation: Centro Algoritmi, Universidade do Minho, 4710-057, Braga, Portugal. jneves@di.uminho.pt.
authors.forename: José
authors.initials: J
authors.lastname: Neves
mesh_terms: D016736:Antiphospholipid Syndrome / Q000175:diagnosis*; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D005260:Female; D006801:Humans; D016571:Neural Networks, Computer; D011247:Pregnancy; D011248:Pregnancy Complications / Q000175:diagnosis*; D015203:Reproducibility of Results; D018570:Risk Assessment
keywords: Antiphospholipid syndrome; Artificial neuronal networks; Knowledge representation and reasoning; Logic programming; Systemic autoimmune diseases