Sano, Autor w serwisie Centre for Computational Personalized Medicine

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Sano News – New issue out now!

AI in medicine, digital twins, microbiome, and more from our latest research and collaborations.

MicrobiomeGPT

Polish AI Project Redefining Gut Microbiome Research

Sano Joins the “Kraków – A Community of Culture” Debate Once Again

Culture in a Time of Change: Who Shapes Its Direction?

Sano co-organised a workshop at the NEURONUS & Young PTBUN Neuroscience Forum

A day dedicated to cutting-edge computational tools in neuroscience and biomedicine

Testing an Angiography Simulator and Strengthening Scientific Collaboration

Sano Visit to Research Partners in Sheffield and London

New book on protein folding and environmental factors

Edited by Prof. Irena Roterman-Konieczna

Co‑authored publication by Adam Sułek in the TOP 10% of SCOPUS

How CARS microscopy and artificial intelligence open new opportunities in precision diagnostics and biomedical research.

Sending warm Easter wishes

from the Sano team

Engineering Bones: A Multiscale Look at Musculoskeletal Health

A Sano Seminar lecture by Gwendolen Reilly explores how engineering and biology come together to understand and treat diseases of the musculoskeletal system.

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Jan K. Argasiński in Onet Wiadomości: how AI can stay ahead of disease

A Sano scientist on the medicine of the future

Sano representatives at a global microbiome conference

Participation in “Microbiome Interactions in Health and Disease 2026” supports networking and knowledge exchange

Sano Representation at ICCS 2026

Sano researchers to present their work in Hamburg

The problem with medical simulations no one talks about

- a new episode of the Twin Things Podcast

Sano participates in Open – H – Embodiment

— a global initiative opening a new chapter in medical robotics and Physical AI

The lesion-tract density index (L -TDI): a survival marker in human GBM. (A) For every subject, the data were normalized to a common template. The T2-weighted image was chosen as the reference modality, and the GBM was inversely masked to discard distorted tissue during the optimization. (B) The normalized tumor mask is used in combination with the whole brain normative tractogram to extract the set of streamlines that intersect the tumor in the same template space as in (A). (C) The lesion-tract density map (L -TDM) provides a unique white matter density map describing the tracts in (B) that interact with the GBM. (D) From the L -TDM, we can define the L -TDI marker by averaging the tract density within the L -TDM binary mask in (C). For a given cohort, the sample can be stratified according to a given percentile. (E) Once a stratification threshold has been set, we conduct thorough tests to assess the discovery of the biomarker. Additional survival analyses on multiple stratification thresholds help determine whether the potential biomarker holds prognostic value. The L -TDI can also be used to characterize both morphological and anatomical landscapes in GBMs, which can be used to understand differences in the survival rates. Once a robust effect has been identified, the L -TDI can be incorporated into standard risk analysis and predictive frameworks to improve patient care.

A non-local diffusion magnetic resonance imaging tract density biomarker to stratify, predict, and interpret survival rates in human glioblastoma

New publication presents a connectomics-based biomarker for predicting glioblastoma survival

Denoising of CT and MRI Images Using Decomposition-Based Curvelet Thresholding and Classical Filtering Techniques

New publication by Mahmoud Nasr, Krzysztof Brzostowski, Rafał Obuchowicz and Adam Piórkowski

Supporting innovation and the future of health technologies in Europe

Sano among partners of Wolves Summit 2026, a leading tech event

Rosmary at the 4th European Congress of Neurology and Neuropsychiatry

A new approach to early diagnosis of cognitive impairment.

Quantum annealing brings modularity maximization and community detection closer to real-world practice

A new paper titled “Modularity Maximization and Community Detection in Complex Networks Through Recursive and Hierarchical Annealing in the DWAVE Advantage Quantum Processing Units” has just been published.

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