Artificial Neural Network Market 2019 | Worldwide Overview By Size, Share, Analysis Emerging Technology, Business Opportunities, Major Company Profiles And Top 10 Regions

Artificial Neural Network Market 2019 | Worldwide Overview By Size, Share, Analysis Emerging Technology, Business Opportunities, Major Company Profiles And Top 10 Regions

“Artificial Neural Network Market Research Report – Forecast to 2023 | MRFRrn”
Global Artificial Neural Network Market Research Report: By Type (Feedback Artificial Neural Network, Feedforward Artificial Neural Network, Other), by Component (Software, Services, Other), by Application (Drug Development, Others) – Forecast Till 2023

Artificial Neural Network Market – Overview

The development and popularity of the concept of machine learning have accelerated the development of artificial neural networks. Market reports connected with the healthcare industry have been presented by Market Research Future which makes reports on other industry verticals that aims to analyze the current market scenarios better. The progress of the market is expected to be spurred by an exceptional CAGR in the duration of the forecast period.

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The prime factors prompting the development of the artificial neural networks are the popularity of artificial intelligence and mounting implementation of the artificial neural network in the healthcare sector. The growing level of hospitalizations around the world is prompting further progress of the market. The development of artificial neuron network-based software is anticipated to create optimistic opportunities for growth in the forecast period.

Market Segmentation

As per MRFR report, the global artificial neural network market is segmented on the basis of type, component and application.

Based on type, it is segmented into feedforward artificial neural network, feedback artificial neural network and others. Of these, the feedforward network is anticipated to have the maximum share in the artificial neural network market.

Based on component, the artificial neural network market is segmented into platform, services and software.

Based on application, it is segmented into drug development, interpretation, bioelectric signal analysis, image analysis & interpretation, clinical diagnosis & prognostics and others

Detailed Regional Analysis

The regional analysis of the artificial neural network market observes that the Americas region is expected to lead the artificial neural network market due to the presence of a well-developed healthcare sector, existence of a large number of enterprises in the expansion of neural network technologies, and a high acceptance of advanced technology in the healthcare sector. The European region is anticipated to control the next principal position in the artificial neural network market. The market development in this region is accredited to the rising acceptance of artificial intelligence among healthcare providers and rising healthcare expenditure together with the growing incidence of chronic diseases.

The Asia Pacific region is projected to reveal the highest growth all over the forecast period due to the heightened economic growth of nations in the region and the mounting need to manage the mounting healthcare expenses. These factors are also accountable for the rising trend towards the digitization of patient records in the healthcare organizations in this region. The Middle Eastern & African region has the lowest stake in the artificial neural network market. Though, this region is likely to have a prospective growth opening for the artificial neural network market through the forecast period. The notable factors motivating the growth rate in this region consist of escalating technological implementations and growing healthcare investments.

Key Players

Key players profiled in the artificial neural network market include Oracle Corporation, IBM Corporation, Microsoft Corporation, Intel Corporation, Qualcomm Technologies, Inc., Neuralware, Google Inc., Alyuda Research, LLC., NeuroDimension, Inc., SAP SE, Ward Systems Group, Inc., Afiniti, SwiftKey, Neural Technologies Limited, and Starmind International AG.

Feb 2019- Researches at the NYU Tandon School of Engineering have come up with an effective machine learning system that will employ ANN (artificial neural network) to predict the behavior of the thermosetting nanocomposites over varied loading rates and range of temperature. This same approach will be applied potentially for predicting the behavior of the thermoplastic materials.

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