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Found 6 papers, 1 papers with code
An Adaptive Computational Intelligence Approach to Personalised Health and Immune Age Characterisation from Common Haematological Markers
Using a learning adaptive algorithm, our model provides a risk assessment score that compares an individual's chronological age from birth to an estimation of a biological immune age derived from the score.
Machine Intelligence-Driven Classification of Cancer Patients-Derived Extracellular Vesicles using Fluorescence Correlation Spectroscopy: Results from a Pilot Study
The RF classifier exhibited a 90% classification accuracy and high sensitivity and specificity in distinguishing the FCS power spectra of cancer patients from those of healthy controls.
A Review of Mathematical and Computational Methods in Cancer Dynamics
Cancers are complex adaptive diseases regulated by the nonlinear feedback systems between genetic instabilities, environmental signals, cellular protein flows, and gene regulatory networks.
Machine Learning Characterization of Cancer Patients-Derived Extracellular Vesicles using Vibrational Spectroscopies
The blood sera of cancer patients are enriched with heterogeneous secretory lipid bound extracellular vesicles (EVs), which present a complex repertoire of information and biomarkers, representing their cell of origin, that are being currently studied in the field of liquid biopsy and cancer screening.
Pattern Detection on Glioblastoma's Waddington landscape via Generative Adversarial Networks
Glioblastoma (GBM) is a highly morbid and lethal disease with poor prognosis.
A Review of Complex Systems Approaches to Cancer Networks
Cancers remain the lead cause of disease-related, pediatric death in North America.
