Fluxus Information

Product catalog summary

Introduction
Avamed Synergy's project, Fluxus, is an AI and deep learning-assisted innovation designed to enhance advanced diagnostics and surgical approaches in oncology. It focuses on understanding the multi-scale nature of cancer cells and predicting tumour growth dynamics using 3D digital twins.

Key Features

AI and DL Integration: Utilizes AI to classify cancer cells based on spatial arrangement and anatomical specificity, improving prediction accuracy of tumour invasion and behaviour.
Dynamic Scaling: Studies geometrical properties of growth fronts, enhancing understanding of tumour growth fluctuations and stochastic evolution.
3D Digital Twins: Provides in vivo study capabilities, allowing detailed analysis of tumour malignancy.

Benefits

For Oncologists: Enhances tumour differentiation accuracy, reduces false negatives by 95%, and improves treatment strategy efficacy by 70%.
For Patients: Offers detailed disease status information, reduces radiation exposure, and improves recovery outcomes. Potential to reduce overdoses and overtreatment by 80% in the next 10-15 years.
For Surgeons: Facilitates surgical planning, reduces surgical time by 30%, and minimizes non-tumour tissue resections by 15%.
For Society: Decreases surgical costs by 12% and overall healthcare costs by 29%, optimizing healthcare resources.

Conclusion
Fluxus represents a paradigm shift in understanding neoplasm evolution, offering substantial improvements in oncology diagnostics and treatment planning.

Catalog excerpts

Our goal is to anticipate tumour growth dynamics and classification, eliminate unwanted complications, improve patient outcomes and reduce costs to healthcare systems. Avamed Synergy Avamed Synergy @AvamedSynergy

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Fluxus, Avamed Synergy's main project, is the first and only AI- and DL-assisted intelligent innovation to aid in advanced diagnostics and surgical approach, enabling in vivo study with 3D digital twins. AI to understand the multi-scale nature of cancer cells and anticipate the dynamics of tumour growth. Allows classification considering the spatial arrangement, anatomical specificity and multiscale nature of cancer cells. More accurate prediction of tumour invasion and behaviour. Dynamic scaling to study geometrical properties of growth fronts or critical points. Better understanding of the...

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