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Philips developers are coding algorithms that help pinpoint cancer



One in three people is expected to have cancer during their lifetime. Using AI-based algorithms, pathologists can make better and faster diagnoses.

New cancer cases will increase by nearly 70% over the next two decades, from 14 million in 2012 to 22 million. In the US, the National Cancer Institute reports that every third person is expected to develop cancer during their lifetime. Pathologists are looking at growing case numbers as patients increasingly expect high-quality diagnoses and treatments, resulting in delays in the delivery of diagnoses.

Pathology, the medical industry that deals with causes, manifestations and diagnoses of diseases such as cancer, has changed little in over a century. With the increasing number and complexity of cancer cases and other diseases, pathology is just beginning to realize the benefits of digitization and AI-enabled productivity and efficiency gains.

The AI ​​Will See You Now

Digitization allows professionals to access a greater amount of medical data to gain a better understanding of their patients and improve outcomes and outcomes. AI continues to help understand this data.

Today, AI is successfully applied to pattern recognition and quantitative measurement of whole slides to detect cancer and other anomalies. In a study, researchers from Case Western Reserve University found that a deep learning system can identify invasive forms of breast cancer in pathological images with 1

00 percent accuracy.

Philips-based software

Philips, a world leader in healthcare technology, has made significant advances in digital and computer-aided pathology (DCP) with the Philips IntelliSite Pathology solution. With this technology, pathologists can more efficiently and accurately diagnose digital images with the support of other clinicians while streamlining workflows.

In 2017, Philips began pioneering the Philips IntelliSite Pathology solution as the first and only digital pathology solution in the US (the largest healthcare market) for primary diagnostic purposes.

Philips introduced its first deep learning product to support accurate tumor assessment for molecular research. The next challenge would be to clinically develop these types of algorithms and seamlessly deploy them in the diagnostic workflow. Seamless clinical use of the AI ​​requires careful workflow considerations, including execution time (more than a few minutes that does not allow for runtime), total deployment costs, and flexibility and control for the pathologist.

What sets Philips apart from other industrial companies?

Philips has partnered with several leading opinion leaders (KOLs) and healthcare providers such as Mount Sinai, a world leader in breast cancer data, and LabPON, which aims to set up the world's largest pathology database with Philips IntelliSite Pathology Solution

With a large curated archive of real medical data, Philips will be able to develop clinically robust deep learning algorithms that can handle the variability of data sources and disease subtypes. These data make it possible for AI solutions to go beyond the proof-of-concept and be used for routine, high throughput practice.

What is it like to work in the area of ​​AI-based health care?

Arun Ananthapadmanabhan, Head of Product at Philips Computational Pathology explains: "AI is everywhere today and data scientists are in demand. The worst thing you can do to a data scientist is to hire him and not provide the right data. Relevant, processed, high quality, curated data is not easy to find and takes a long time to build. "

" There are many ways to use AI in healthcare, "adds Philips Data Scientist Ariadne Whitby. "It's an exciting work-to-work domain, as demonstrated by the many AI-based health technology startups and the advances made by established players. It's great to see the many innovative ideas and companies. "

Whitby came to DCP Philips because he combined the best of both worlds – a dynamic startup environment supported by a strong parent company. "I wanted to join an organization where there is domain knowledge to understand how a new product or concept can be integrated into the healthcare system and the distribution channels. I did not want to risk working on something great, which is not realized because of the lack of commercial know-how. "

" Healthcare AI and especially digital pathology is one of Philips priorities, "says Arun. "Digital pathology combines the power of a startup with our experience and rich heritage of innovation. We continue to grow fast and our teams are young, diverse and highly skilled. They wake up every day and think about the next step in solving the global cancer problem, "he concludes.

Get Ready

The digital transformation of pathology is in full swing, with AI assisting subjectivity through sophisticated to replace quantitative measurements as state-of-the-art technologies and data-driven solutions improve the reliability and quality of diagnoses, treatments, and patient care.

These deep learning systems can not be used without the help of software talent, creating ground-breaking career opportunities for software developers and end-users Data scientists who want to change the future of healthcare Are you ready?

This entry was submitted by Philips .


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