Gissa Chatbot: uma proposta de Agente Conversacional Inteligente RASA Open-Source para assistência no período gestacional

• Ano de defesa: 2023
• Autor(a) principal: Gomes, Kamila Amélia Sousa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Agente Conversacional; Chatbot; Gestantes; Inteligência Artificial; Processamento de Linguagem Natural; Saúde; Conversational Agent; Pregnant women; Artificial intelligence; Natural Language Processing; Health
• Link de acesso: http://repositorio.ufc.br/handle/riufc/75013

With the population’s constant demand in the health sector for specialized care, aggravated by the difficulty of immediate access and the overload of services, the need for alternatives that allow the dissemination of reliable and easily accessible information becomes even more critical, especially when They consider themselves to be people with chronic illnesses and compromised immunity, such as pregnant women. Technology plays an essential role in providing solutions that became even more evident during the pandemic period, improving the quality of care and allowing relevant information to be delivered remotely and instantly, ensuring adequate care and the well-being of pregnant women and of the entire population. In this context, this work proposes the implementation of a chatbot using Artificial Intelligence (AI) and Natural Language Processing (NLP) through the Rasa framework, aiming to improve care during the gestational period. Interaction with the chatbot occurs through the Telegram messaging platform, providing quick and reliable access, providing a more comprehensive experience throughout the pregnancy, through relevant and timely information. This personalized and interactive approach aims to promote the autonomy and well-being of pregnant women, offering additional support during this crucial phase. To evaluate its effectiveness, a questionnaire was used with the collaboration of ACS (Community Health Agents) at the Padre Palhano Family Health Center (CSF), in the city of Sobral, through the SUS usability test (System Usability Scale). Thus, the implementation of the solution promotes the instant dissemination of accurate information, benefiting pregnant women and strengthening the health system. The positive results obtained from user testing and cross-validation highlight the effectiveness and positive impact of this innovative approach to pregnancy health care.