Objective: This study aims to evaluate the efficacy of wearable physiology and movement sensors in identifying a spectrum of challenging behaviors, including self-injurious behavior (SIB), in children and teenagers with autism spectrum disorder (ASD) in real-world settings.
Approach: We utilized a long-short-term memory (LSTM) network with features derived using the wavelet scatter transform to analyze physiological biosignals, including electrodermal activity and skin temperature, alongside three-dimensional movement data captured via accelerometers. The study was conducted in naturalistic environments, focusing on participants' daily activities.
In optical imaging of solid tumors, signal contrasts derived from inherent tissue temperature differences have been employed to distinguish tumor masses from surrounding tissue. Moreover, with the advancement of active infrared imaging, dynamic thermal characteristics in response to exogenous thermal modulation (heating and cooling) have been proposed as novel measures of tumor assessment. Contrast factors such as the average rate of temperature changes and thermal recovery time constants have been investigated through an active thermal modulation imaging approach, yielding promising tumor characterization results in a xenograft mouse model.
View Article and Find Full Text PDFGuidelines suggest the Liver Imaging Reporting and Data System (LI-RADS) may not be applicable for some populations at risk for hepatocellular carcinoma (HCC). However, data assessing the association of HCC risk factors with LI-RADS major features are lacking. To evaluate whether the association between HCC risk factors and each CT/MRI LI-RADS major feature differs among individuals at-risk for HCC.
View Article and Find Full Text PDF