Artificial Neural Networks in Medicine

2022 ◽  
pp. 1491-1509
Author(s):  
Steven Walczak
Keyword(s):  
Neural Networks ◽  
Resource Allocation ◽  
Artificial Neural Networks ◽  
Cost Reduction ◽  
Decision Problems ◽  
The Future ◽  
Recent Trends ◽  
Artificial Neural ◽  
Medical Domain ◽  
Future Direction

Artificial neural networks (ANNs) have proven to be efficacious for modeling decision problems in medicine, including diagnosis, prognosis, resource allocation, and cost reduction problems. Research using ANNs to solve medical domain problems has been increasing regularly and is continuing to grow dramatically. This chapter examines recent trends and advances in ANNs and provides references to a large portion of recent research, as well as looking at the future direction of research for ANN in medicine.

Artificial Neural Networks in Medicine

2021 ◽  
pp. 1901-1918
Author(s):  
Steven Walczak
Keyword(s):  
Neural Networks ◽  
Resource Allocation ◽  
Artificial Neural Networks ◽  
Cost Reduction ◽  
Decision Problems ◽  
The Future ◽  
Recent Trends ◽  
Artificial Neural ◽  
Medical Domain ◽  
Future Direction

Artificial neural networks (ANNs) have proven to be efficacious for modeling decision problems in medicine, including diagnosis, prognosis, resource allocation, and cost reduction problems. Research using ANNs to solve medical domain problems has been increasing regularly and is continuing to grow dramatically. This chapter examines recent trends and advances in ANNs and provides references to a large portion of recent research, as well as looking at the future direction of research for ANN in medicine.

Applications of Artificial Neural Networks in Economics and Finance

2018 ◽  
pp. 6631-6641
Author(s):  
Iva Mihaylova
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Research Trends ◽  
Dependence Analysis ◽  
Future Trends ◽  
Powerful Technique ◽  
Analytic Tool ◽  
The Future ◽  
Multivariate Dependence ◽  
Artificial Neural

Artificial neural Networks (ANNs) are a powerful technique for multivariate dependence analysis. Originally inspired by neuroscience, ANNs are becoming an increasingly attractive analytic tool for applications in the area of economics and finance due to the flexible solutions they offer. The purpose of this article is to present such important applications with an emphasis on recent research trends. The contributions are grouped as follows: ANNs (1) for prediction, (2) for classification and (3) for modelling. The chapter concludes with the future trends in the ANNs research in economics and finance.

scholarly journals The Use of Artificial Neural Networks to Assess the Capacity of Transport Measures

2015 ◽  
Vol 10 (1) ◽  
pp. 47-56
Author(s):  
Artur Duchaczek ◽  
Dariusz Skorupka
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Decision Problems ◽  
Logistics Management ◽  
Computer Application ◽  
Computational Algorithms ◽  
Practical Application ◽  
Artificial Neural

Abstract In the area of logistics management both managers and engineers rely primarily on proven computational algorithms, for this reason, it is often difficult to convince them to the use of artificial neural networks in solving decision problems. The paper presents the possibilities of using the FANN library in building of a computer application applied in the area of logistics. The possibilities of the component are presented on the example of applications of artificial neural networks to estimate the capacity of transport vehicles based on their dimensions. The example presented in the work was solved with the use of a multi-network Layered Perceptron. The example depicted not only the possibility of using artificial neural networks for solving poorly structured tasks but also practical application of the TFannNetwork component

scholarly journals PREDIKSI PENGADAAN DAN PENGELOLAAN INVENTORI JARINGAN SYARAF TIRUAN ALGORITMA BACKPROPAGATION PADA PERUM BULOG

KOMPUTEK ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Ethan Mahesa Murty
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Food Availability ◽  
Public Company ◽  
The Future ◽  
Rice Consumption ◽  
Food Stability ◽  
Artificial Neural ◽  
Prediction Techniques

Perum Bulog is a state-owned public company in food logistics field. Perum Bulog has a duty to stabilize food availability in Indonesia. The most consumed food by Indonesians is rice. It is estimated that the total national rice consumption reaches 30.25 million tons of rice. In this way, Perum Bulog must be able to meet their rice stock to maintain national food stability. However, in fact, in 2019 as many as 20 thousand tons of domestic rice had gone bad and caused the company to lose up to 167 billion. Thus, it is important to make predictions to determine the amount of rice stock in the future. One of the prediction techniques that can be used is prediction using Artificial Neural Networks. This study aims to determine the future rice stock of Perum Bulog using Artificial Neural Networks. Perum Bulog merupakan perusahaan umum milik negara yang bergerak di  bidang logistik pangan.  Perum Bulog memiliki tugas untuk menstabilkan ketersediaan pangan di Indonesia. makanan pokok yang paling sering dikonsumsi masyarakat Indonesia adalah beras. Diperkirakan jumlah konsumsi beras nasional mencapai 30,25 juta ton beras. Dengan begitu Perum Bulog harus dapat memenuhi stok beras mereka untuk menjaga kestabilan pangan nasional. Namun, nyatanya dilapan pada tahun 2019  sebanyak 20 ribu ton beras dalam negeri mengalami pembusukan dan membuat perusahaan rugi hingga 167 miliar. Dengan begitu pentingnya melakukan prediksi  untuk mengetahui jumlah stok beras dimasa depan. Salah satu teknik prediksi yang dapa digunakan adalah prediksi menggunakan jaringan syaraf tiruan. Penelitian ini bertujuan untuk mengetahui stok beras masa depan Perum Bulog menggunakan jaringan syaraf tiruan.

Applications of Artificial Neural Networks in Economics and Finance

2019 ◽  
pp. 997-1008 ◽  
Author(s):  
Iva Mihaylova
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Research Trends ◽  
Dependence Analysis ◽  
Future Trends ◽  
Powerful Technique ◽  
Analytic Tool ◽  
The Future ◽  
Multivariate Dependence ◽  
Artificial Neural

Artificial neural networks (ANNs) are a powerful technique for multivariate dependence analysis. Originally inspired by neuroscience, ANNs are becoming an increasingly attractive analytic tool for applications in the area of economics and finance due to the flexible solutions they offer. The purpose of this chapter is to present such important applications with an emphasis on recent research trends. The contributions are grouped as follows: ANNs (1) for prediction, (2) for classification, and (3) for modelling. The chapter concludes with the future trends in the ANNs research in economics and finance.

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