x-focus.ai is an artificial intelligence company
dedicated to improve healthcare
x-focus.ai Solutions
Radiology - Pathology - Neurophysiology
x-focus neuro
- AI Based Volumetric Analysis & Monitoring of Brain MRI Images
- AI Based WMH Lesion Detection on Brain MRI Images
- Module in use
x-focus pulmnod
- AI-powered Solution for Pulmonary Nodule Detection
- Module in use
x-focus pulthormb
- Pulmonary Thromboembolism Detection and Analysis
- Module at Test Phase
x-focus mln
- Mediastinal Lymph Node Detection and Analysis
- Module under development
x-focus idl
- Interstitial Lung Diseases Detection and Analysis
- Module under Development
x-focus prostate
- Segmentation of prostate gland and zones
- Module under Development
x-focus path
- Detection of CMV at histopathology images
- Module in use
x-focus neurophys
- Module under Development
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x-focus.ai combines best in class medical expertise with cutting edge AI capabilities to ensure precision and speed
Developed with best in class AI experts, Radiologist and other Medical Doctors
I have been working with the x-focus.ai team for over 2 years in the field of nodule detection systems. Their scientific approach, as well as their process-oriented AI solutions using the latest technologies, are very successful
Associate Professor MD Sinem Gezer
Dokuz Eylül University Medical Faculty
Department of Radiology
Artificial intelligence algorithms are greatly beneficial in helping us detect diseases by performing fast and efficient analyses within radiological images. We have been working with the x-focus.ai team for over 2 years to create the most effective algorithms
Associate Professor Ender Konukoglu
Biomedical Image Computing at ETH Zurich
Head of Computer Vision Laboratory
It is possible to achieve fast and efficient results in the field of radiology by using artificial intelligence. I am extremely pleased to be part of the work in interstitial lung diseases with the x-focus.ai team
Associate Professor MD Gamze Durhan
Hacettepe Üniversitesi Medical Faculty
Department of Radiology