Neural Networks Architecture Evaluation in a Quantum Computer

In this work, we propose a quantum algorithm to evaluate neural networks architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The proposed algorithm is based on a quantum associative memory and the learning algorithm for artificial neural networks. Unlike conventional algorithms for evaluating neural network architectures, QNNAE does not depend on initialization of weights. The proposed algorithm has a binary output and results in 0 with probability proportional to the performance of the network. And its computational cost is equal to the computational cost to train a neural network

Redes neurais lógicas quânticas

Através da miniaturização dos componentes dos chips a cada ano a velocidade dos computadores é aproximadamente duplicada. Esta rápida redução dos componentes dos chips é conhecida como a Lei de Moore. Apesar de se manter verdadeira nos últimos anos, a lei de Moore está se aproximando de seu limite, pois os componentes dos chips estão se aproximando a escala atômica. Neste momento, será necessário considerar os efeitos da mecânica quântica sobre a computação. O estudo dos modelos de computação não convencionais, como a computação quântica, é um dos grandes desafios da pesquisa em computação no Brasil. O desenvolvimento de novos hardwares com tecnologias diferentes do silício pode ter consequências nas técnicas de desenvolvimento de hardware e software. O objetivo desta dissertação é investigar que vantagens podem ser obtidas através da aplicação de técnicas da computação quântica no desenvolvimento e treinamento de modelos de redes neurais artificiais. Três modelos de redes neurais quânticas baseados em modelos de redes neurais sem pesos foram propostos. Ao contrário dos outros modelos de redes neurais quânticas, as redes propostas nesta dissertação podem simular as redes em que foram baseadas. A principal vantagem dos modelos quânticos neurais propostos nesta dissertação está no seu algoritmo de treinamento, um algoritmo onde a rede neural é executada apenas uma vez independente do tamanho do conjunto de treinamento e da rede neural. O algoritmo proposto foi baseado em uma memória associativa quântica e no algoritmo de busca de Grove

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p<0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status