Base de Datos CONASS

Using machine learning to assess potential cases of transthyretin cardiac amyloidosis in Brazil: a retrospective database approach

Laper, Isabella Zuppo; Camacho-Hubner, Cecilia; Ferreira, Rafaela Vansan; Souza, Claudenice Leite Bertoli de; Simões, Marcus Vinícius; Fernandes, Fabio; Correia, Edileide de Barros; Abreu, Ariane de Jesus Lopes de; Julian, Guilherme Silva.

Value health; 26 (12 suppl), 2023

INTRODUCTION: Amyloidosis is a group of protein misfolding disorders leading to organ damage due to insoluble amyloid fibril deposits • The two primary types of cardiac amyloidosis are light-chain amyloid (AL) and transthyretin (TTR) cardiac amyloidosis • TTR amyloidosis can be hereditary (hATTR) or ...

Pré-Albumina, d0000695500, d0023180, d0010240, d0063330, Amiloidose Familiar

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An automated machine learning method to efficientlyclassify the 12-lead ECG signal acquisition quality

O. Júnior, Vandemberg M; Evangelista, Vitor R; Baronetti, Ramon; Uemoto, Vinicius R; Gomes, Danielo G; De Marchi, Mariana F. N; Freitas, Renata V; Madeiro, João P. V.

ABSTRACT: Given their low cost and non-invasive nature, ElectroCardioGram(ECG) signals have been widely used as a useful tool for diagnosing heart dis-eases. However, acquisition issues such as electrode interchange and oscilla-tion noise may negatively impact expert exam interpretation and even ...

d0000695500, d0045620, Cardiopatias

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Comparação de algoritmos de aprendizado de máquina na classificação do infarto do miocárdio usando detecção de sinal de elevação do segmento ST no eletrocardiograma e dados clínicos
Comparison of machine learning algorithms in the classification of myocardial infarction using ST-segment elevation signal detection in electrocardiogram and clinical data

Mota, Diandro M. B; Filho, Fabiano; Woelffel, Marlon; Farias, Bruno; Almeida, Mariana; Burgard, Christoph; Ferreira, Izabelle; Kuster, Gustavo; Lopes, Jose H.

Rev. Soc. Cardiol. Estado de Säo Paulo; 33 (supl. 2B), 2023

INTRODUÇÃO: As doenças cardiovasculares (DCVs) são as principais responsáveis por mortes no mundo. A incorporação de novas tecnologias utilizando Inteligência Artificial (IA) surge como potencial aliada para a otimização do manejo dessas doenças. No entanto, ainda há a necessidade de aumentar...

d0004650, d0000695500, d0039330, d0045620, d0000726570, d0011850

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