Evidence map›Paper›PMID 41139734›Full record

ArticleJournal of medical systems2025

K-operator for Modelling Neurodegeneration: Simulations, fMRI Application, Eigenvalue Analysis and Recurrence Plots.

Sofia Fazio, Patrizia Ribino, Francesca Gasparini, Norbert Marwan, Peppino Fazio, Marco Gherardi, Maria Mannone

Abstract read
In one paragraph

Article in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sofia FazioDipartimento di Fisica, Università Statale di Milano, Milano, Italy.
Patrizia RibinoICAR, National Research Council of Italy (CNR), Palermo, Italy.
Francesca GaspariniDipartimento di Informatica, Sistemistica e Comunicazione, Università degli Studi di Milano-Bicocca, Milano, Italy.
Norbert MarwanResearch Department Complexity Science, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany.
Peppino FazioDipartimento di Scienze Molecolari e Nanosistemi (DSMN), Ca' Foscari University of Venice, Venezia, Italy.
Marco GherardiDipartimento di Fisica, Università Statale di Milano, Milano, Italy.
Maria MannoneICAR, National Research Council of Italy (CNR), Palermo, Italy. maria.mannone@uni-potsdam.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brain network damage provoked by a neurological disease can be modelled as the result of the action of an operator, K, acting on the brain, inspired by physics. Here, we explore the matrix formulation of K, analysing eigenvalues and eigenvectors, with heuristic considerations on different techniques to approximate it. The primary objective of this paper is to lay the foundational groundwork for an innovative framework aimed at the development of predictive models regarding the progression of neurodegenerative diseases. This endeavour will leverage the potential of integrating these novel representations of brain damage with advanced machine-learning techniques. A case study based on real-world data is presented here to support the proposed modelling.

Indexed as

BrainMagnetic Resonance ImagingModels, NeurologicalNeurodegenerative DiseasesComputer SimulationHumansMachine LearningAlzheimer-Perusini’s disease progressionFunctional networkK-operatorParkinsonpredictive models

Identifiers

PMID41139734
PMCPMC12554825

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.