Artificial intelligence in healthcare
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Artificial intelligence in healthcare
 
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Leveraging AI for the future of healthcare poses challenges

Our Al-powered solutions address major challenges that are facing the healthcare field. Right now, the demand for diagnostic services is outpacing the supply of experts in the workforce. Developing solutions for managing this ever-increasing workload is a crucial task for the healthcare sector. Moreover, as the workload is growing, diagnostics and treatment are also becoming more complex. Diagnostic experts and physicians need a new set of tools that can handle large volumes of medical data quickly and accurately, allowing you to make more objective treatment decisions based on quantitative data and tailored to the needs of the individual patient. To provide this new toolset, we will need to draw on the power of artificial intelligence (AI).

Shaping the future of digital health with our AI-powered solutions

AI is a key technology for digitalizing healthcare and enables you to transform care delivery, expand precision medicine and improve the patient experience. We have developed a portfolio of more than 45 AI-powered solutions that help to automate and standardize not only workflows but also complex diagnostics to meet the needs of the individual patient. We are now entering the next era of AI-powered solutions. Learn more about our latest AI-powered offerings that will shape the future of healthcare:

Key concepts of AI at a glance

Artificial intelligence (AI) is a computer-aided process for solving complex problems that are usually reserved for humans. More specifically, it involves machines mimicking cognitive functions typically associated with the human brain.1 Some examples are machine vision, pattern recognition, speech recognition, and knowledge-based decision-making in the broader sense. Distinctions are made here between classic algorithms, which follow paths that are permanently fixed by the programmer, and applications of machine learning which identify solutions independently based on supplied data.

A special role is played by what is know as “deep learning”, which goes beyond what traditional machine learning algorithms can achieve. These algorithms are trained and improved by continuously adding high volumes of data, equipping them to keep improving their error rate performance expectations.

Machine learning enables the machine to adapt to new circumstances and to detect and extrapolate patterns.1 Machine learning can be further divided into traditional machine learning and deep (machine) learning.

Traditional machine learning uses algorithms that are: hand-crafted, hard-coded, and designed to look for specific features. These are “specialized” and cannot easily be re-used for different tasks.

Deep (machine) learning is a type of machine learning that uses multilayer neural networks with multiple hidden layers between the input and output layers. These algorithms can identify relationships that may not have been recognized using traditional techniques.

Why we are a reliable partner for AI-powered solutions

We are the global leader when it comes to AI patent applications in healthcare and have been a pioneer in AI development for more than 20 years. We own more than 500 patent families related to machine learning, of which more than 125 are rooted in deep learning. With established AI expertise, future-oriented staff, vast medical data sets, and the exceptional computing power needed for creating algorithm-supported healthcare solutions, we are the right partner when venturing into the world of AI. We have what it takes to leverage AI into clinical routine:

See AI healthcare technology in action

Watch this video to see our AI technology in action and listen to our experts explaining the key challenges in healthcare today.

AI is more than just a buzzword

Watch this video to see our AI technology in action and listen to our experts explaining the key challenges in healthcare today.

Deep learning algorithms explained

Watch this video to learn how deep learning algorithms can simplify and enhance the accuracy of certain medical procedures

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1Russell & Norvig, Artificial Intelligence. 2016.