Maicon Herverton Lino Ferreira da Silva Barros

TL;DR: This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process.

TL;DR: This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process.

TL;DR: This work-inprogress has as its main goal the integration of two Brazilian health databases in order to improve the quality of tuberculosis mortality data and a phonetic encoding technique and a pattern matching recognition technique are proposed as solutions and results compared.

TL;DR: In this paper , the authors present an exploratory data analysis on data regarding technological extension projects, designed by the Secretariat of Science, Technology and Innovation of the State of Pernambuco (from Portuguese, Secretaria de Ciência, Tecnologia e Inovação do Estado de Pernmbuco, SECTI) and the Pernavuco Foundation for the Support of Science and Technology (From Portuguese, Fundação de Amparo à CiÃncia e TecnOLOGia de B.ººº e Úncia de P.º 1ºº 3º Úº 4ºº 2º Ô 4º ê 5º Bº ë 5º â 6º á 7º Ó 6º 2” 3º 5º 2.