AI and Deep Learning
in Cancer Diagnosis
Medical Image + Deep Learning Algorithm = Faster Cancer Diagnosis with Better Efficacy
AI digital Pathology
Pathoplatform – faster and better tissue examination
AI digital Radiology
Radiology Platform – greater productivity in DICOM analysis
Custom AI Algorithm
Deep Learning and Artificial Intelligence on your service
How can AI and Deep Learning help to detect cancer?
AI and Deep Learning used in Cancer Diagnosis make whole treatment much more efficient. That is to say, specialized algorithmic solutions analyze medical images for pathology and radiology. Firslty, it is faster and better than human accuracy. Secondly, solutions are accesible both in API and Web Platforms. Above all, applications are designed to offer faster and better access for second and third diagnostic opinions. In short, benefits are numerous for all involved groups.
- Store vast amounts of image
- View images from many access points simultaneously
- Improve doctor to doctor cooperation within the organization as well as outside
- Make use of computer aided intervention tools and share the results easily
- Increase output by detecting more cases in less time
- Improve patient outcomes thanks to personalized therapies
- Enhance service quality – faster and accurate diagnosis
- Save on cost and time by reducing patient length-of-stay and minimizing resources required to treat a patient
- Enhance staff satisfaction by reducing manual, repetitive tasks and preventing physician burn out
- View picture as a data
- Work more efficiently and diagnose more patients in less time by speeding up case review
- Describe every image with a plurality of relevant attributes like: size, location and morphology
- Use a formal, accessible, shared, and broadly applicable language for diagnose representation
- Extract qualitative and quantitative characteristics out of medical images using different modalities including CT, MR, PET, etc.
- Exchange knowledge
- Improve accuracy and compare diagnosis
- Get more free time for rest… or more complex cases
- Compare with algorithmic solutions
- See other cases
- Share experience with other patients
- Get your diagnosis and results faster
- Receive more effective treatment thanks to precise diagnosis and personalized therapies
- No more misdiagnosis and unnecessary surgeries or procedures
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MRI Analysis - case study Cancer Center performed MRI Analysis of brain tumor to compare radiology and pathology classification. Firstly, we researched and built a segmentation mechanism for the MRI scans (ROI selection). Secondly, we researched and built a classifier...
Cancer Center on Startup World Cup & Summit Once again we are pleased to say that Cancer Center got into V4 finals of the Startup World Cup & Summit. SWCSummit is another one of the most significant prestigious startup events in Europe and Cancer Center will...