Cognitive Computing

Global Cognitive Computing and Artificial Intelligence Systems in Healthcare Market is expected to huge growth during forecast period 2019 to 2025. Cognitive Computing and Artificial Intelligence Systems in Healthcare Market report includes key factors driving growth of cognitive computing and artificial intelligence systems in healthcare. The market for cognitive computing and artificial intelligence systems in healthcare is mainly segmented into five major components: type of offering, technology, application, end user and geography.

 

Top Key Player of Cognitive Computing and Artificial Intelligence Systems in Healthcare Market:-

Carestream, Fujifilm Medical Systems, GE Healthcare, Philips Healthcare and Siemens Healthcare

The report efficiently examines the most noteworthy subtle elements of the Cognitive Computing and Artificial Intelligence Systems in Healthcare Market with the assistance of a comprehensive and specialized investigation. Characterized in a ground-up way, the report shows a broad outline of the market based on the elements that are expected to have an impressive and quantifiable effect on the market’s developmental circumstances over the estimated timeframe.

The research report, Cognitive Computing and Artificial Intelligence Systems in Healthcare Market offers a clear understanding of the subject matter. The report has been amassed using the principal and subordinate research methodologies. Both these methods are aimed towards cooperating precise and particular data pertaining the market dynamics, historical events, and the current market picture. Moreover, the report also includes a SWOT analysis that determines the strengths, weaknesses, prospects, and threats impacting the segments of the overall market.

 

This market research report on the Global Cognitive Computing and Artificial Intelligence Systems in Healthcare Market is an all-encompassing study of the business sectors up-to-date frameworks, industry enrichment drivers, and manacles. It provides market forecasts for the coming years. It contains an analysis of late amplifications in innovation, Porter’s five force model analysis and advanced profiles of hand-picked industry competitors. The report additionally articulates a survey of minor and full-scale factors charging for the new candidates in the market and the ones as of now in the market along with a systematic value chain exploration.

The manufacturers responsible for increasing the sales of Cognitive Computing and Artificial Intelligence Systems in Healthcare Market have been mentioned to get a wide-ranging information about the production. Different online and offline activities have been scrutinized, which are beneficial to get global clients rapidly. The report further studies the impact of SWOT analysis and Porter’s five model on the progress of this market.

 

Table of Content:-

Cognitive Computing and Artificial Intelligence Systems in Healthcare Market Research Report 2019-2025.

Chapter 1: Industry Overview

Chapter 2: Cognitive Computing and Artificial Intelligence Systems in Healthcare Market International and Market Analysis

Chapter 3: Environment Analysis of Cognitive Computing and Artificial Intelligence Systems in Healthcare.

Chapter 4: Analysis of Revenue by Classifications

Chapter 5: Analysis of Revenue by Regions and Applications

Chapter 6: Analysis of Cognitive Computing and Artificial Intelligence Systems in Healthcare Market Revenue Market Status.

Chapter 7: Analysis of Cognitive Computing and Artificial Intelligence Systems in Healthcare Industry Key Manufacturers

Chapter 8: Sales Price and Gross Margin Analysis

Chapter 9: Marketing Trader or Distributor Analysis of Cognitive Computing and Artificial Intelligence Systems in Healthcare.

Chapter 10: Development Trend of Cognitive Computing and Artificial Intelligence Systems in Healthcare Market 2019-2025.

Chapter 11: Industry Suppliers of Cognitive Computing and Artificial Intelligence Systems in Healthcare with Contact Information

Chapter 12: New Project Investment Feasibility Analysis of Cognitive Computing and Artificial Intelligence Systems in Healthcare

Chapter 13: Conclusion of the Cognitive Computing and Artificial Intelligence Systems in Healthcare Market Research Report

Source: A Market Report

 

Cognitive computing is the end of one-size-fits-all education. The technology will make possible this declarationby Ignacio Estrada: If a child can’t learn the way we teach, maybe we should teach the way the child learns.

This is exactly what will be possible in the near future with the help of cognitive computing.

IBM defines cognitive computing as “systems that learn at scale, reason with purpose and interact with humans naturally. Cognitive computing uses self-teaching algorithms, data mining, computer vision, and natural language processing to solve problems.”

These systems are poised to optimize human operations in education as well as other industries.

IBM Watson is an example of a cognitive computing system being deployed in education. The IBM cognitive computing system is able to communicate using natural language.

The ability of these kinds of systems to digest large data sets and communicate with humans in natural language will greatly expand a teacher’s teaching scope.

You know how embarrassing it can be for a teacher when a bright spark asks a question that the teacher can’t answer? Well, with Watson or similar cognitive systems, those moments will be something of the past.

The teacher can simply direct the question to the cognitive system, which will come up with the right answer to the question together with an explanation of how it arrived at the answer.

One enduring frustration in teaching is the fact that teachers are frequently faced with students who vary in their ability to absorb new information. In addition to different aptitudes and different learning styles, students often have different levels of motivation to learn.

In fact, there are so many variables in one classroom; it’s a wonder so many students do learn something.

It is simply impossible for a teacher to always give each student their deserved attention at their level. So, some learners inevitably fall through the cracks, which can have dire consequences for them later when they arrive at the point where they have to decide what career they want to follow.

The arrival of intelligent agents in the classroom will put an end to this frustrating problem.

Cognitive agents will learn every detail about each student: their aptitude, abilities, interests, and preferred learning style. And they will use this information to personalize course work for each student.

The system would, for instance, know what the student’s learning style is. Imagine a child is a kinesthetic learner with an aversion to math. The cognitive computing system will create a study plan to help the child master math problems in a way which incorporates some physical activity.

These cognitive systems would also notice when a learner is not coping with the study materials. The system can then adapt the learning materials to suit the learner’s pace and abilities. It will also alert the teacher to the situation so appropriate action can be taken.

In this way, cognitive agents will help teachers to reach more students more effectively.

With the help of cognitive computing, teaching is about to become both easier and more exciting, but most of all, more effective.

Source: The Tech Advocate

What is cognitive computing?

As per wikipedia meaning: Cognitive computing (CC) describes technology platforms that, broadly speaking,
are based on the scientific disciplines of artificial intelligence and signal processing.

Sub components of Cognitive Computing systems

Natural Language Processing

 - understand meaning and context in a language, allowing deeper, more intuitive level of discovery and even interaction with information.

Machine Learning – Algorithms that help train the system to recognize images and understand speech

Algorithms that learn and adapt with Artificial Intelligence

Deep Learning – to recognize patterns

Image recognition – like humans but more faster

Reasoning and decision automation – based on limitless data

Emotional Intelligence

Real world examples and usecases of Cognitive Computing:

ANZ bank of Australia used Watson-based financial services apps to offer investment advice,
by reading through thousands of investments options and suggesting best-fit based on customer specific profiles, further taking into consideration their age,
life stage, financial position, and risk tolerance.

Geico is using Watson based cognitive computing to learn the underwriting guidelines, read the risk submissions, and effectively help underwrite

Brazilian bank Banco Bradesco is using Cognitive assistants at work helping build more intimate, personalized relationships

Out of the personal digital assistants we have Siri, Google Now & Cortana – I feel Google now is much easy and quickly adapt to your spoken language.

There is a voice command for just about everything you need to do — texting, emailing, searching for directions, weather, and news. Speak it; don’t text it!

Refrences:

Wikipedia.

http://bigdata-madesimple.com/

 

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