A motor imagery brain-computer interface connects the human brain and computers via electroencephalography (EEG). However, individual differences in the frequency ranges of brain activity during motor imagery tasks pose a challenge, limiting the manual feature extraction for motor imagery classification. To extract features that match specific subjects, we proposed a novel motor imagery classification model using distinctive feature fusion with adaptive structural LASSO.
View Article and Find Full Text PDFObjective: To establish a model for predicting the disease-specific survival (DSS) of patients with oral squamous cell carcinoma (OSCC).
Methods: Patients diagnosed with OSCC from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into development (n = 14,495) and internal validation cohort (n = 9625). Additionally, a cohort from a hospital located in Southeastern China was utilized for external validation (n = 582).
Objective: To assess the prognostic role of pretreatment lymphocyte percentage (LY%) for patients with oral squamous cell carcinoma (OSCC).
Methods: A large-scale prospective cohort study between July 2002 and March 2021 was conducted. Propensity score-matched (PSM) analysis and inverse probability of treatment weighting (IPTW) analysis were performed to adjust for potential confounders.
J Acoust Soc Am
February 2017
Ultrasonic elliptical vibration cutting (UEVC) is effective in ultraprecision diamond cutting of hard-brittle materials and ferrous metals. However, its design is quite empirical and tedious. This paper proposes an analytical design method for developing the UEVC device which works at the Flexural-Flexural complex-mode to generate the elliptical vibration.
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