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The Most Trending AI in Healthcare Industry Now

Let’s see the most trending AI in healthcare industry now. The trend of large health companies are integrating with AI which needs large data accessibility. Larger health data put down the foundations for implementation of AI algorithms.

The trendiest AI application in the healthcare industry now is image recognition software. This software is used to identify specific objects or features in digital images. It is used to diagnose medical conditions, to plan surgery, and to improve patient care.

One of the most common applications of image recognition software in healthcare is to identify cancerous tumours. By identifying tumours early, doctors can provide treatment that can save lives. Image recognition software is also used to diagnose other medical conditions, such as heart disease and Alzheimer’s Disease.

In addition to diagnosing medical conditions, image recognition software is also used to plan surgery. By using image recognition software to map the patient’s anatomy, doctors can plan surgery with greater accuracy. This can lead to fewer complications and shorter recovery times for the patient.

Finally, image recognition software can be used to improve patient care. By tracking a patient’s condition over time, doctors can see how they are responding to treatment. This helps doctors to make changes to the patient’s treatment plan if necessary.

A large part of industry emphasis of implementation of AI in the healthcare industry that depends upon the clinical decision support systems. As great data is collected, machine learning algorithms could be more adaptable and could resulting more durable acknowledgements and services.

Many big companies are investigating the feasibility of the incorporation of big data in the healthcare industry. These companies are looking into the market circumstances through the domain of data evaluation, storage, management, and testing technologies which are all key terms of the healthcare industry.

The followings are examples of a few big companies contributing to AI algorithms for use in healthcare:

1. IBM’s Watson Health

The study and treatment of tumours are in development at Memorial Sloan Kettering Cancer Center and Cleveland Clinic. IBM is working with CVS Health along with Johnson & Johnson on AI applications in incurable diseases treatment and on analysis of scientific research papers to find new links for drug evolution.

In May 2017, IBM and Rensselaer Polytechnic Institute started a joint project “Health Empowerment by Analytics, Learning and Semantics (HEALS)”, to investigate enhancing healthcare using AI technology.

2. Google’s DeepMind

UK National Health Service is using Google’s DeepMind platform to detect certain health risks probabilities through data collected via a mobile apps. Another project with the NHS brings in developing computer vision algorithms to detect cancerous tissues with the analysis of medical images collected from NHS patients.

3. Microsoft’s Hanover project

Oregon Health & Science University’s Knight Cancer Institute and Microsoft are in partnership in Hanover project comprises medical research to predict the most effective cancer drug treatment alternatives for patients. Other projects include medical image analysis of tumour chain and the development of programmable cells.

4. Intel’s Investments

Intel’s venture capital arm Intel Capital recently invested in startup Lumiata which uses AI to identify at-risk patients and develop healthcare possibilities.

5. AI Medical Innovation System (AIMIS)

AI Medical Innovation System (AIMIS) uses to utilize AI-powered diagnostic medical imaging service, Tencent Doctorwork and WeChat Intelligent Healthcare.

6. Tencent (China)

Tencent is working on several medical AI systems and services. They have a huge investment in healthcare areas.

7. Qure.ai

Qure.ai which emphasises on utilization of deep learning and AI to upgrade radiology and accelerate the investigation of diagnostic x-rays. Qure.ai is now deploying AI-powered pandemic response solutions for COVID-19 management.

8. Kheiron Medical

Kheiron Medical has developed deep learning AI to investigate breast cancers in mammograms.

9. Elon Musk

Elon Musk is making his interpretation for the surgical robot that could embed the Neuralink brain chip. Neuralink belongs to next generation neuroprosthetic which are detailed interfaces with thousands of neural roots in the brain. It allows a chip, a very tiny size , to be inserted in place of a chunk of skull by a precision surgical robot with accuracy to avoid accidental injury or other mishap.

10. Trend of Consultancy AI

Babylon Health Services UK is going famous in digital consultants. GP at Hand, Ada Health, AliHealth Doctor You, KareXpert and Your.MD(The self-care app) are also using AI frequently to give medical consultation based on common medical knowledge and patients medical history.

11. Xiao Man

Xiao Man robot made by IFlytek launched which unified artificial intelligence technology to identify the registered customer and provide personalised guidance in medical areas.

12. Cruzr

It works in the field of medical imaging, identify the registered customer and provide personalised recommendations in medical field. Cruzr is made by UBTECH.

13. Pepper

It also works in the same way as Cruzr works as mentioned above in the areas of medical imaging, identify the registered customer and provide personalised recommendations in medical areas. Softbank Robotics is its creator.

14. Several AI for Coronavirus Records

There are several AI models which collect coronavirus data from websites and organisations which are willing to provide their data.

AI Competition

Large tech companies such as Apple, Google, Amazon, and Baidu all have their own AI research divisions spending millions of dollars granted for acquisition of smaller AI based companies as the market for AI expanding constantly.

Automobile manufacturers giants such as Tesla, BMW, Toyota, GE and Volvo are beginning to use machine learning healthcare in their cars as well because all have new research campaigns to find ways of learning a driver’s vital stats to make sure whether they are awake, paying attention to the road, or not under the influence of some drugs or in emotional stress.

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