The healthcare industry continues to be a major driver of the U.S. economy, with more than $3.5 trillion spent on healthcare in 2018 alone.
Copyright by www.business.com
Researchers believe that the industry will contribute more than $5.6 trillion to the economy by 2025 as well.
Much of this revenue comes from the medical research field, which is responsible for improving drug research, disease diagnosis and treatment protocols. Major research companies are collaborating with software development services to integrate deep learning technology into their investigations.
Deep learning promises to transform the way that doctors review medical tests and make diagnoses, helping them identify diseases and start treatment quicker. The technology will also help pharmaceutical companies develop life-saving drugs in a shorter amount of time.
What is deep learning?
Deep learning is a niche in the machine learning field. Machine learning is an innovative branch of computer science that combines artificial intelligence (AI) and traditional science with mathematics and statistics to create a powerful technology that can learn from experience.
Major companies in the retail, banking and logistics industries are already working with software development companies and using the technology to save money, increase efficiency and plan for the future.
Machine learning is premised on the idea that computer engineers should be able to do more than just code a program – they should be able to teach computers how to write their own programs. Additionally, these “intelligent” computers should be capable of learning from past experiences to improve their skills and the quality of their predictions.
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Deep learning takes things a step further by mimicking the structure of the human brain, which is layered, or “deep.” It emulates this layered structure by creating a similar, artificial neural network with the potential to be even more powerful than cutting-edge machine learning software.
For example, the transportation industry is using deep learning to teach computers how to recognize images. The autonomous car startup Wayve.ai taught its cars how to quickly and accurately recognize road conditions by exposing the system to millions of images of roadways. Medical companies are using the same tactics to transform their own industry.
How deep learning is transforming medical research
This type of active learning is vital for the medical research industry. That’s because computers can learn from new medical research and past performance data to improve the quality and accuracy of diagnoses.
Deep learning will transform the medical research industry by introducing more advanced data analysis into research efforts and by eliminating the need for a human expert with years of training.
This cutting-edge technology is also expected to reduce the time needed to make a diagnosis. Rather than spending several months or more going from specialist to specialist, patients will soon work with their physician to enter their symptoms and test results into a computer.
The deep learning program will use data points from millions of other patients to produce accurate diagnosis months or even years before a human doctor could. This will help reduce patient anxiety and improve healthcare outcomes through early treatments. […]
Read more – www.business.com
The healthcare industry continues to be a major driver of the U.S. economy, with more than $3.5 trillion spent on healthcare in 2018 alone.
Copyright by www.business.com
Much of this revenue comes from the medical research field, which is responsible for improving drug research, disease diagnosis and treatment protocols. Major research companies are collaborating with software development services to integrate deep learning technology into their investigations.
Deep learning promises to transform the way that doctors review medical tests and make diagnoses, helping them identify diseases and start treatment quicker. The technology will also help pharmaceutical companies develop life-saving drugs in a shorter amount of time.
What is deep learning?
Deep learning is a niche in the machine learning field. Machine learning is an innovative branch of computer science that combines artificial intelligence (AI) and traditional science with mathematics and statistics to create a powerful technology that can learn from experience.
Major companies in the retail, banking and logistics industries are already working with software development companies and using the technology to save money, increase efficiency and plan for the future.
Machine learning is premised on the idea that computer engineers should be able to do more than just code a program – they should be able to teach computers how to write their own programs. Additionally, these “intelligent” computers should be capable of learning from past experiences to improve their skills and the quality of their predictions.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Deep learning takes things a step further by mimicking the structure of the human brain, which is layered, or “deep.” It emulates this layered structure by creating a similar, artificial neural network with the potential to be even more powerful than cutting-edge machine learning software.
For example, the transportation industry is using deep learning to teach computers how to recognize images. The autonomous car startup Wayve.ai taught its cars how to quickly and accurately recognize road conditions by exposing the system to millions of images of roadways. Medical companies are using the same tactics to transform their own industry.
How deep learning is transforming medical research
This type of active learning is vital for the medical research industry. That’s because computers can learn from new medical research and past performance data to improve the quality and accuracy of diagnoses.
Deep learning will transform the medical research industry by introducing more advanced data analysis into research efforts and by eliminating the need for a human expert with years of training.
This cutting-edge technology is also expected to reduce the time needed to make a diagnosis. Rather than spending several months or more going from specialist to specialist, patients will soon work with their physician to enter their symptoms and test results into a computer.
The deep learning program will use data points from millions of other patients to produce accurate diagnosis months or even years before a human doctor could. This will help reduce patient anxiety and improve healthcare outcomes through early treatments. […]
Read more – www.business.com
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