RODRIGO DA SILVA DIAS
Projetos de Pesquisa
Unidades Organizacionais
LIM/21 - Laboratório de Neuroimagem em Psiquiatria, Hospital das Clínicas, Faculdade de Medicina
6 resultados
Resultados de Busca
Agora exibindo 1 - 6 de 6
- Telemental health in Brazil: past, present and integration into primary care(2015) DIAS, Rodrigo Da Silva; MARQUES, Andrea De Fatima Horvath; DINIZ, Paula Rejane Bezerra; SILVA, Tatiana Araújo Bertilino Da; COFIEL, Luciana; MARIANI, Mirella Martins De Castro; SALGADO, Christiana Leal; OLIVEIRA, Ana Emilia Figueiredo De; MIGUEL FILHO, Euripedes Constantino; WEN, Chao Lung; NOVAES, Magdala De Araújo; TAVARES, HermanoBackground Telemental Health Care has reported very good results and is included within mental health priorities by the World Health Organization. Objective To provide an overview of the current situation of the integration of Brazilian telemedicine activities into primary health care. Methods Critical review based on MEDLINE database, using the keywords “telemedicine”, “primary health care” “mental health” and “telemental health”, on websites of the Brazilian Ministry of Health and Brazilian Telehealth Network Program, and on personal communication. Results The Brazilian Telehealth Network Program is well positioned and connects primary health care with academic centers. Regulations standards allow a broader scope of activities for psychologists, however, are more restrictive for physicians. In Brazil most of telemental health activities are focused on education and second opinion consulting. A huge challenge must be overcome considering the regional differences and the telehealth implementation experience. Research initiatives have been initiated both in the implementation and evaluation of the mental health assistance into primary health care. Discussion Brazilian Telemental Health initiatives into Primary Care are aligned with other examples around the world, have a great potential for improving mental health care service delivery, and access to proper mental health care, especially if articulated in a national program and coordinated research.
conferenceObject Premenstrual mood symptoms after menarche association with early onset and perinatal mood disorders in women with bipolar disorder - fidings from STEP-BD(2015) DIAS, R.; LAFER, B.; SACHS, G. S.; NIERENBERG, A. A.; JOFFE, H.- Rapid cycling bipolar disorder is associated with a higher lifetime prevalence of migraine(2015) GIGANTE, A. D.; BARENBOIM, I. Y.; DIAS, R. da S.; TONIOLO, R. A.; MIRANDA-SCIPPA, A.; KAPCZINSKI, F. P.; LAFER, B.
- Generating facial emotions for diagnosis and training(2015) TESTA, Rafael L.; MUNIZ, Antonio H. N.; CARPIO, Liseth. U. S.; DIAS, Rodrigo S.; ROCCA, Cristiana C. A.; MACHADO-LIMA, Ariane; NUNES, Fatima L. S.The ability to process and identify facial emotions is an essential factor for an individuals social interaction. There are certain psychiatric disorders that can limit an individuals ability to recognize emotions in facial expressions. This problem could be confronted by making use of computational techniques in order to develop learning environments for the diagnosis, evaluation and training in identifying facial emotions. This paper presents an approach that uses image processing techniques, formal languages, anthropometry and Facial Action Coding System (FACS) to generate caricatures that represent facial movements related to neutral, satisfaction, sadness, anger, disgust, fear and surprise emotions. The rules that define the emotions were determined using an AND-OR graph to enable generating these images in a flexible manner. An evaluation conducted with healthy volunteers showed that some emotions are more easily recognized, while for other emotions the caricatures need to be further improved. This is a promising approach, since the parameters used provide flexibility to define the emotional intensity that must be represented.
- A Multi-Relational Model for Depression Relapse in Patients with Bipolar Disorder(2015) SALVINI, Rogerio; DIAS, Rodrigo da Silva; LAFER, Beny; DUTRA, InesBipolar Disorder (BD) is a chronic and disabling disease that usually appears around 20 to 30 years old. Patients who suffer with BD may struggle for years to achieve a correct diagnosis, and only 50% of them generally receive adequate treatment. In this work we apply a machine learning technique called Inductive Logic Programming (ILP) in order to model relapse and no-relapse patients in a first attempt in this area to improve diagnosis and optimize psychiatrists' time spent with patients. We use ILP because it is well suited for our multi-relational dataset and because a human can easily interpret the logical rules produced. Our classifiers can predict relapse cases with 92% Recall and no-relapse cases with 73% Recall. The rules and variable theories generated by ILP reproduce some findings from the scientific literature. The generated multi-relational models can be directly interpreted by clinicians and researchers, and also open space to research biological mechanisms and interventions.
conferenceObject A multi-relational model for depression relapse in patients with bipolar disorder by means of a machine learning approach(2015) DIAS, R.; SALVINI, R.; DUTRA, I.; LAFER, B.