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
Diagnostics
(Imaging, Pathology, Sequencing)
(Imaging, Pathology, Sequencing)
Clinical decision making
Data management
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.
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
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
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
Easy to use
AI benefits under single platform to existing clinical workflow environment.
Assisted detection
Detection and identification for faster diagnostic reading of medical images.
Early detection
Early warning and intelligent alerts of abnormalities in challenging radiology images.
Support diagnosis
Assist with first-time-right diagnosis of radiology images and quantification of findings for reporting.
Multiple modalities
One scalable and future proof platform that grows and evolves with your specific needs.
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.
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
"How AI can bring productivity to medical imaging?"
An interview with Philips executive, Homer Pien
News and blogs on AI
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![Insights at scale: a how-to for healthcare leaders]()
June 15, 2022
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![Why the future of healthcare is (mostly) in the cloud]()
June 09, 2022
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![CEO Frans van Houten on the transformation of healthcare]()
March 11, 2022
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![CEO Frans van Houten on innovations shaping the future of healthcare]()
February 02, 2022
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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