AI Manager

AI Manager

Enable artificial intelligence capabilities for your radiology department

AI Manager

Enable artificial intelligence capabilities for your radiology department

Implementation of Artificial Intelligence (AI) in healthcare will be a true revolution. Philips AI solutions, such as AI Manager, will help implementing AI and improving hospital operations and patient care”

M.A. van Buchem

Chairman, Department of Radiology - Leiden University Medical Center (LUMC)

Empower your radiology department with Artificial Intelligence.

At Philips, we believe that Artificial Intelligence (AI) should be combined with a deep human understanding of the clinical and operational context so that it is able to enhance the people who use it, not replace them.

 

We provide an end-to-end AI enablement solution that integrates with your existing IT infrastructure and PACS solution that enables your radiologists to leverage AI applications for more comprehensive assessment and gain deeper clinical insights in your radiology workflow.

Discover the endless possibilities

What is the most important application of AI for healthcare professionals?1

34 percent radial icon

Diagnostics
(Imaging, Pathology, Sequencing)

21 percent radial icon

Clinical decision making

11 percent radial icon

Data management

8 percent radial icon

Operational management

Benefits for your enterprise2

We enable healthcare providers to easily implement AI apps into their workflows – including apps from third parties – via a common cloud-based platform, AI Manager, with easy access to a large portfolio of validated third party AI algorithms that integrate seamlessly in the existing radiology workflow, available through a common commercial channel, HealthSuite Marketplace.

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One single AI platform

  • AI enablement and clinical application deployment
  • Reduced integration effort for all your AI applications
  • One advanced vendor agnostic, multi-modality platform
  • Single access point for all AI generated results
  • Fully scalable certified cloud-based solution

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A Trusted Partner

  • Flexible business model, via a SaaS offering
  • AI procurement, accounting and billing utilizing HealthSuite Marketplace
  • Data processing in a single trusted Philips environment
  • Installation, set up and user training for AI manager
  • Maintenance, updates and customer support

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Deeper Clinical Insights 

  • Effortless generation of all relevant AI results
  • Harmonized AI result representation
  • Opportunistic screening to detect incidental findings
  • Assists with detection [3, 4] and faster diagnostic reading [5] of medical imaging
  • Precision diagnostics by objective quantification

Discover what′s in it for you

Ease of use icon

Easy to use

AI benefits under single platform to existing clinical workflow environment.

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Assisted detection

Detection and identification for faster diagnostic reading of medical images.

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Early detection

Early warning and intelligent alerts of abnormalities in challenging radiology images.

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Support diagnosis

Assist with first-time-right diagnosis of radiology images and quantification of findings for reporting.

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Multiple modalities

One scalable and future proof platform that grows and evolves with your specific needs.

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Automated Reports

Automatic quantification reports and Prepopulated Reporting Template in DICOM SR or encapsulated DICOM format.

Speak to an expert

Contact our solution expert for the full list of product features and discover how Philips AI Manager can empower your radiology department with the latest clinical AI applications.

Speak to an expert icon

Frequently Asked Questions - Your questions, answered

Events and resources

Philips Live! forum

Explore our latest innovations and insights in radiology through an amazing program of webinars, symposia and keynote presentations, brought directly to you.

Bodymap of Clinical AI apps

Clinical AI solutions to augment and empower people, with appropriate human supervision.

Key publications

Our latest scientific publications about our AI research methods and results.

AI Manager - Efficiently leverage AI in your daily clinical routine

Fully scalable solution to host and execute multiple AI applications on a single study to support you with more comprehensive assessment and deeper clinical insights.

Using AI to meet operational and clinical goals

For healthcare IT leaders there is an opportunity to use AI to address operational efficiencies and support clinical decision making.

Spearhead the change

How to integrate and benefit from clinical AI applications while retaining clinician control.

"How AI can bring productivity to medical imaging?"
An interview with Philips executive, Homer Pien

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Philips apreciază şi respectă confidenţialitatea clienţilor săi. Vă puteţi retrage permisiunile în orice moment. Pentru mai multe informaţii, citiţi Politica de confidenţialitate Philips.

News and blogs on AI

1 EIT Health and McKinsey – Transforming Healthcare with AI

2Some products are only available in selected countries. Philips AI Manager is not intended for data interpretation or diagnosis. Availability of 3rd party algorithm may vary per market. The functionalities and benefits of the solution depends on customer-specific configuration and use. Please contact your local Philips representative for market availability.

3 Improved detection of lung nodules with novel software that suppresses the rib and clavicle shadows on chest radiographs. Radiology. July 2011. 260, 265-273. By Freedman M., Lo B., Seibel J., and Bromley E. 
4 Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study. RSNA, May 4, 2021. By Duron L, Ducarouge A., Gillibert A., Lainé J., Allouche C., Cherel N., Zhang Z., Nitche N., Lacave E., Pourchot A., Felter A., Lassalle L., Regnard N-E., Feydy A.
5 Computer-Aided Detection of Lung Nodules of CT with a Computerized Pulmonary Vessel Suppressed Function. American Journal of Roentgenology 2018, 210:3, 480-488. By Lo S., Freedman M., Gillis L., White C., Mun S.

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