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Utilização da Inteligência Artificial (Machine Learning) para Avaliação Prognóstica da Degenerescência Mixomatosa da Válvula Mitral em Cães
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Abstract(s)
O presente artigo de revisão tem como objetivo reunir e analisar os estudos mais recentes
sobre a aplicação da inteligência artificial (IA) no contexto da doença degenerescência mixomatosa da
válvula mitral (DDMVM) em cães. Especificamente, esta revisão propõe uma análise crítica da
integração da IA na prática clínica veterinária, com foco na sua utilidade para a formulação do
prognóstico em pacientes diagnosticados com esta patologia cardíaca.
Neste sentido, este trabalho apresenta uma síntese dos métodos de IA atualmente utilizados, por meio
da revisão das principais técnicas disponíveis. A revisão contempla ainda as diversas áreas da saúde —
tanto na medicina humana como na veterinária — em que a IA já se encontra implementada. A partir
dessas aplicações, é explorado o potencial da aprendizagem automática (machine learning) na
avaliação prognóstica de cães com DDMVM.
Por fim, são discutidas as principais limitações e potencialidades associadas à utilização desta
tecnologia emergente na prática clínica veterinária, com vista à sua futura consolidação como
ferramenta de apoio ao diagnóstico e à decisão terapêutica.
This review article aims to compile and analyse the most recent studies on the application of artificial intelligence (AI) in the context of myxomatous mitral valve disease (MMVD) in dogs. Specifically, it provides a critical evaluation of the integration of AI into veterinary clinical practice, focusing on its potential utility in prognostic assessment of patients diagnosed with this cardiac condition. Accordingly, this work offers an overview of the AI methodologies currently in use, through a comprehensive review of the main existing techniques. It also examines the various domains within healthcare—both human and veterinary medicine—where AI has already been implemented. Based on these applications, the potential of machine learning for assisting in the prognostic evaluation of dogs with MMVD is explored. Finally, the study discusses the main limitations and strengths associated with the adoption of this emerging technology in veterinary clinical settings, aiming to support its future consolidation as a diagnostic and therapeutic decision-making tool.
This review article aims to compile and analyse the most recent studies on the application of artificial intelligence (AI) in the context of myxomatous mitral valve disease (MMVD) in dogs. Specifically, it provides a critical evaluation of the integration of AI into veterinary clinical practice, focusing on its potential utility in prognostic assessment of patients diagnosed with this cardiac condition. Accordingly, this work offers an overview of the AI methodologies currently in use, through a comprehensive review of the main existing techniques. It also examines the various domains within healthcare—both human and veterinary medicine—where AI has already been implemented. Based on these applications, the potential of machine learning for assisting in the prognostic evaluation of dogs with MMVD is explored. Finally, the study discusses the main limitations and strengths associated with the adoption of this emerging technology in veterinary clinical settings, aiming to support its future consolidation as a diagnostic and therapeutic decision-making tool.
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Keywords
Inteligência artificial Machine Learning Degenerescência mixomatosa da válvula mitral Cães Diagnóstico Prognóstico Medicina veterinária Artificial intelligence Mitral valve disease Dogs Diagnostic Prognostic Veterinary Medicine