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IAssist - Medical Assistant

Grant number: 20/05779-0
Support Opportunities:Research Grants - Innovative Research in Small Business - PIPE
Duration: April 01, 2021 - December 31, 2021
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:André Gustavo Cavalcanti de Melo
Grantee:André Gustavo Cavalcanti de Melo
Host Company:IAssist Desenvolvimento de Programas Ltda
CNAE: Desenvolvimento e licenciamento de programas de computador customizáveis
Atividades de atenção ambulatorial executadas por médicos e odontólogos
Atividades de serviços de complementação diagnóstica e terapêutica
City: São Paulo
Associated researchers:André Fujita ; Luiz Fernando Lopes ; Mariangela Correa ; Miriam Galvonas Jasiulionis ; Vladmir Cláudio Cordeiro de Lima
Associated grant(s):21/12040-3 - IAssist - Medical Assistant, AP.PIPE
Associated scholarship(s):21/02711-8 - IAssist: medical assistant, BP.PIPE
21/03055-7 - IAssist: medical assistant, BP.TT
21/03048-0 - IAssist: medical assistant, BP.TT


Today, the amount of health-related information is doubling every two years worldwide. In 2020, this volume will double every 73 days. To keep up to date in his/her specialty, a medical doctor needs to study more than 160 hours a week. As in other medical specialties, this fact is also creating an even greater knowledge gap between oncologists and non-oncologists. There is no doubt that defining the correct diagnosis is an objective pursued by doctors of all specialties and a professional and ethical duty for their patients. Most neoplasms have a high chance of cure, if diagnosed and treated early. In addition to primary prevention, in which risk factors can be controlled, early detection can also reduce mortality caused by the illness. The delay in diagnosis and the shortage of specialists are among the main factors that contribute to the increase in cancer mortality rates in Brazil. This scenario highlights the need to develop actions that favor access to qualified medical information, especially in places with poor resources and an insufficient number of doctors and specialists. Tools based in Artificial Intelligence (AI) represent an effective solution to aid the diagnosis process, although they are still in the initial stage of maturation, considering the complexity of the decision-making process in clinical settings. Thus, the objective of this project is to develop an application software based on AI, to be used by the medical community, especially located in regions with a shortage of resources and medical professionals specialized in oncology. The application uses data from cancer reference centers, such as the Hospital de Amor (new name for the Hospital de Câncer de Barretos), to process clinical and laboratory data of patients, in order to suggest possible diagnostics of various types of cancer for the doctors who perform the primary care, which normally do not have enough knowledge in oncology. In this way, it is possible to refer the patient to a referral center in the shortest possible time. Among the target customers for this product are clinics, hospitals and other public and private health services. (AU)

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