Το iToBoS είναι ένα ερευνητικό έργο που χρηματοδοτείται από το πρόγραμμα έρευνας και καινοτομίας της Ευρωπαϊκής Επιτροπής Horizon 2020, στο θέμα "Ψηφιακή διαγνωστική - Ανάπτυξη εργαλείων για την υποστήριξη κλινικών αποφάσεων ενσωματώνοντας διάφορα είδη διαγνωστικών δεδομένων".
The most updated source for worldwide cancer data is represented by the GLOBOCAN 2020 report of the International Agency of Cancer Research (IACR).
The scientific work "Finding and removing Clever Hans: Using explanation methods to debug and improve deep models", with the support of iToBoS project, has been published.
DICOM stands for Digital Imaging and COmmunications in Medicine: it is an international standard related to the exchange, storage and communication of digital medical images and other related digital data.
Over the last half century, clinicians and researchers have made enormous advances in detecting and treating melanoma.
The scientific work "Explain and improve: LRP-inference fine-tuning for image captioning models.", with the support of iToBoS project, has been published.
Machine learning and specifically deep learning, have dramatically improved the state-of-the-art in many areas of research, including computer vision, speech recognition, and natural language processing.
[GE] Hautkrebs: Forscher der Universität Hannover entwickeln neuen, intelligenten Ganzkörper-Scanner
In this document we present a video on the development of optics for the new generation of scanners of the iToBoS project. The document is in German.
PhoenixD member Prof. Dr. Bernhard Roth and his team are part of the iToBoS project, which the European Union funds with twelve million euros.
If today privacy is mainly discussed in the contexts of maintaining databases and leaks from them, in the near future it will grab headlines and the attention of companies even when it comes to learning and training the machine. The arcile is writen in Hebrew.