Natural Language Processing

Global Natural Language Processing (Nlp) Market Report presents an irreplaceable and sheer analysis for Natural Language Processing (Nlp) industry. The study report comprises evaluation of numerous influential factors including industry overview in terms of historic and present situation, key manufacturers, product/service application and types, key regions and marketplaces, forecast estimation for global market share, revenue and CAGR.

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The report also sheds light on the evaluation of growth opportunities, challenges, market threats and constraining factors of the market. It studies local regional as well as global market and emerging segments, and market dynamics also. Additionally, it offers insight into the competitive landscape, market driving factors, industrial environment, and the latest and upcoming technological advancements to determine the overall scenario of industry and move forward to form lucrative business strategies effortlessly.

Major Players in Natural Language Processing (Nlp) Market are :

  • NetBase Solutions
  • Apple Incorporation
  • 3M
  • Microsoft Corporation
  • Verint Systems
  • IBM Incorporation
  • Dolbey Systems
  • SAS Institute Inc.
  • Google
  • HP

Most widely used downstream fields of Natural Language Processing (Nlp) Market covered in this report are :

  • Automotive
  • Healthcare
  • Banking Financial Services and Insurance (BFSI)
  • IT and Telecom
  • Defense & Aerospace
  • Others

Along with key manufacturers, their profiles, global market share, production volume, gross sales margin, revenue, manufacturing plants, and their capacities, material sourcing strategy, newly implemented technologies are also discussed in this report.

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It is focused on active contenders in Natural Language Processing (Nlp) industry and provides analysis for their production methodologies, manufacturing plants, and capacities, product cost, raw material sources, value chain analysis, effective business plans, product/service distribution pattern. Player’s profiling including product specification, sales, gross margin, share in the global market, revenue, and CAGR also.

If you have any customized requirement need to be added regarding Natural Language Processing (Nlp) , we will be happy to include this free of cost to enrich the final study.

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Read Source Artice BY STANLEY DailyIndustryUpdates

#AI #NLP #NetBaseSolutions, #AppleIncorporation #DataAnalytics

A natural language processing system helped identify lumbar spine imaging findings, providing significant gains in model sensitivity, according to a study in Academic Radiology.

Researchers evaluated an NLP system built with open-source tools for identifying lumbar spine imaging findings related to low back pain on MRI and X-ray radiology reports from four health systems. The study authors selected 871 reports to form a reference-standard dataset, and four spine experts annotated the presences of 26 findings.  

The researchers calculated inter-rater agreement and finding prevalence from the annotated data, which was split into development (80 percent) and testing (20 percent) sets. The study authors developed an NLP system from both rule-based and machine-learned models, and the system with validated using accuracy metrics such as sensitivity, specificity and area under the receiver operating characteristic curve.

The researchers concluded the NLP system performed well in identifying the 26 lumbar spine findings. Machine-learned models provided substantial gains in model sensitivity with only a slight loss of specificity and overall higher AUC. 

More articles on spine:
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Spine surgery's biggest misconception debunked by Dr. Issada Thongtrangan
Leadership in a competitive market: Cleveland Clinic's Dr. Michael Steinmetz on the trends in spine today + the qualities he looks for in tomorrow's leaders

Written by Shayna Korol 

Read Source Article BeckersSpine

#AI #NLP #NaturalLanguageProcessing #Datasets


In basic terms, Natural language processing or NLP is the ability of the system to understand the human language spoken to it, analysing the words and taking actions according to its analysis. It is widely used in various areas such as machine translation, speech processing and many others.

 This technology has been around for a couple of years now and has gone unnoticed by the public until now. NLP has seen massive developments recently in this sector to improve and enhance the experience of customer interaction with other humans, bots etc. Moreover, there have been improvements to increase the efficiency of this system for search, bots as well as the user interface which has made it a priority for quite a lot of users.

Applications of Natural Language Processing: -

The most common applications of NLP are as follows-

  1. Smarter search: -

Gone are the days that people used to search content using the search engines by entering keywords, topic names etc. With the recent developments by many tech giants such as Google which has included NLP in its search function which now enables the people to speak out the content, they want to search.

Moreover, data can be explored in a better way by speaking rather than changing settings, applying filters etc. to get the desired content.

  1. Chabot’s: -

Chabot’s is the easiest method of presenting the consumer with the desired information almost immediately. The clubbing of NLP with Chabot’s is what made it all possible. The most practical example of this technology is finding a right product by letting the Chabot know your desired quantity, size and colour, performing self-serving tasks such as personal banking etc.

NLP provides a more personalized look and feel to the customer-Chabot interaction.

  1. Voice User Interface: -

The best and most used application of NLP is virtual personal assistants that have been rolled out by the companies to help the people search and perform tasks by the use of their voice such as Alexa. Alexa is loaded with tons of features and capabilities that can be controlled by you by a simple question by you.

The future?

The new era of natural language processing has already begun. Now the humans need not adapt to the new technology, now the technology is smart enough to adapt to the humans. There have been several reports that in the recent years more than fifty percent of the tasks will be performed with the help of NLP rather than typing etc.


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