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Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents

Su-Hsin Huang, Joon-Khim Loh, Jinn-Tsong Tsai, Ming-Feng Houg et al. • Chinese Journal of Cancer (2017)

Abstract Background Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40880-017-0192-9

A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections

Alma Y. Alanis, Gustavo Munoz-Gomez, Nancy F. Ramirez, Oscar D. Sanchez et al. • Algorithms (2024)

This work introduces an impulsive neural control algorithm designed to mitigate the spread of epidemic diseases. The objective of this paper is the development of a vaccination strategy based on a PIN-type impulsive controller based on an o...

DOAJ Open Access (DOAJ) DOI: 10.3390/a17120577

ỨNG DỤNG MẠNG NƠ-RON NHÂN TẠO ĐỂ ĐIỀU KHIỂN THIẾT BỊ BẰNG GIỌNG NÓI TIẾNG VIỆT

Nguyễn Chí Ngôn, Trần Thanh Hùng, Trương Thị Thanh Tuyền, Nguyễn Thái Nghe • Tạp chí Khoa học Đại học Cần Thơ (2005)

Bài báo đề cập đến một giải pháp ứng dụng mạng nơ-ron nhân tạo (Artificial neural networks) để điều khiển thiết bị bằng giọng nói tiếng Việt. Phép biến đổi Fourier thời gian ngắn - STFT (Short time Fourier Transform) được áp dụng để trích c...

DOAJ Open Access (DOAJ)

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks

Yaoda Xu, Maryam Vaziri-Pashkam • NeuroImage (2022)

Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural ne...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.neuroimage.2022.119635

Neural Networks and Brain Function

Edmund T. Rolls, Alessandro Treves • Oxford University Press eBooks (1997)

The aim of this book is to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. The book is structured in three sectio...

OPENALEX DOI: https://doi.org/10.1093/acprof:oso/9780198524328.001.0001

Neural Network Acceptability Judgments

Alex Warstadt, Amanpreet Singh, Samuel R. Bowman • Transactions of the Association for Computational Linguistics (2019)

This paper investigates the ability of artificial neural networks to judge the grammatical acceptability of a sentence, with the goal of testing their linguistic competence. We introduce the Corpus of Linguistic Acceptability (CoLA), a set ...

OPENALEX cc-by DOI: https://doi.org/10.1162/tacl_a_00290

Kalman Filtering and Neural Networks

• Wiley eBooks (2001)

From the Publisher: Kalman filtering is a well-established topic in the field of control and signal processing and represents by far the most refined method for the design of neural networks. This book takes a nontraditional nonlinear appr...

OPENALEX DOI: https://doi.org/10.1002/0471221546

Artificial Neural Networks

Ajith Abraham • Wiley eBooks (2005)

Abstract Artificial neural networks are useful tools that have been applied successfully in a broad range of signal‐processing problems. From a signal‐processing perspective, their ability to adapt continuously to new data allows them to tr...

OPENALEX DOI: https://doi.org/10.1002/0471497398.mm421

An Introduction to Convolutional Neural Networks

Keiron O’Shea, Ryan Nash • arXiv (Cornell University) (2015)

The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of art...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1511.08458