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Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.
JCO Clin Cancer Inform
January 2025
Machine Learning Department, H. Lee Moffit Cancer Center and Research Institute, Tampa, FL.
Purpose: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evaluated whether an auxiliary data set could improve prediction performance.
View Article and Find Full Text PDFMeasurement properties of instruments to assess insight in psychosis: A systematic review protocol.
PLoS One
January 2025
Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America.
Introduction: Insight in psychosis, defined as a patient's awareness and judgment of their mental illness, is a complex and evolving concept. Historically, the absence of insight was considered a defining characteristic of psychosis, but recent decades have seen the development of structured tools for its assessment. This systematic review aims to critically appraise the measurement properties of instruments used to assess insight in individuals with schizophrenia spectrum, bridging the gap between theoretical conceptualization and clinical practice.
View Article and Find Full Text PDFA novel feature extraction method based on dynamic handwriting for Parkinson's disease detection.
PLoS One
January 2025
School of Computer Science and Engineering, Changchun University of Technology, Changchun, Jilin, China.
Parkinson's disease (PD) is a common disease of the elderly. Given the easy accessibility of handwriting samples, many researchers have proposed handwriting-based detection methods for Parkinson's disease. Extracting more discriminative features from handwriting is an important step.
View Article and Find Full Text PDFTransitions in intensive care: Investigating critical slowing down post extubation.
PLoS One
January 2025
Department of Computer Science, University College London, London, United Kingdom.
Complex biological systems undergo sudden transitions in their state, which are often preceded by a critical slowing down of dynamics. This results in longer recovery times as systems approach transitions, quantified as an increase in measures such as the autocorrelation and variance. In this study, we analysed paediatric patients in intensive care for whom mechanical ventilation was discontinued through removal of the endotracheal tube (extubation).
View Article and Find Full Text PDFBiases in Volumetric Versus Surface Analyses in Population Receptive Field Mapping.
Hum Brain Mapp
February 2025
BCBL - Basque Center on Cognition Brain and Language, Donostia - San Sebastián, Spain.
Population receptive field (pRF) mapping is a quantitative functional MRI (fMRI) analysis method that links visual field positions with specific locations in the visual cortex. A common preprocessing step in pRF analyses involves projecting volumetric fMRI data onto the cortical surface, typically leading to upsampling of the data. This process may introduce biases in the resulting pRF parameters.
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