ArticleJournal of advanced research2021
Lung cancer dynamics using fractional order impedance modeling on a mimicked lung tumor setup.
Article in Journal of advanced research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 34 citations in OpenAlex.
- Classification of lung cancer tissue using bioimpedance spectroscopy and fractional-order circuit modeling.Physical and engineering sciences in medicine · 2026Article
- Tracking control of air flow based on a fractional-order model of the lung impedance.Scientific reports · 2025Article
- CMINNs: Compartment model informed neural networks - Unlocking drug dynamics.Computers in biology and medicine · 2025Article
- A study on fractional tumor-immune interaction model related to lung cancer via generalized Laguerre polynomials.BMC medical research methodology · 2023Article
- Model Calibration of Pharmacokinetic-Pharmacodynamic Lung Tumour Dynamics for Anticancer Therapies.Journal of clinical medicine · 2022Article
- Liquid biopsy in lung cancer: significance in diagnostics, prediction, and treatment monitoring.Molecular cancer · 2022Review
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
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Abstract
Introduction: As pulmonary dysfunctions are prospective factors for developing cancer, efforts are needed to solve the limitations regarding applications in lung cancer. Fractional order respiratory impedance models can be indicative of lung cancer dynamics and tissue heterogeneity. Objective: The purpose of this study is to investigate how the existence of a tumorous tissue in the lung modifies the parameters of the proposed models. The first use of a prototype forced oscillations technique (FOT) device in a mimicked lung tumor setup is investigated by comparing and interpreting the experimental findings. Methods: The fractional order model parameters are determined for the mechanical properties of the healthy and tumorous lung. Two protocols have been performed for a mimicked lung tumor setup in a laboratory environment. A low frequency evaluation of respiratory impedance model and nonlinearity index were assessed using the forced oscillations technique. Results: The viscoelastic properties of the lung tissue change, results being mirrored in the respiratory impedance assessment via FOT. The results demonstrate significant differences among the mimicked healthy and tumor measurements, ( Conclusion: Simulation tests comparing the changes in impedance support the research hypothesis. The impedance frequency response is effective in non-invasive identification of respiratory tissue abnormalities in tumorous lung, analyzed with appropriate fractional models.
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