Yongsen Chen
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Author Swipe
View article: Deep learning-based segmentation of acute ischemic stroke MRI lesions and recurrence prediction within 1 year after discharge: A multicenter study
Deep learning-based segmentation of acute ischemic stroke MRI lesions and recurrence prediction within 1 year after discharge: A multicenter study Open
The MRA-UNet model can effectively improve the segmentation accuracy of MRI. The model, which was established by combining radiomics features and clinical factors, held some value for predicting AIS recurrence within 1 year.
View article: Malnutrition is associated with severe outcome in elderly patients hospitalised with COVID-19
Malnutrition is associated with severe outcome in elderly patients hospitalised with COVID-19 Open
Some studies have identified influencing factors of COVID-19 illness in elderly, such as underlying diseases, but research on the effect of nutritional status is still lacking. This study retrospectively examined the influence of nutrition…
View article: The relationship between the Barthel Index and stroke-associated pneumonia in elderly patients and factors of SAP
The relationship between the Barthel Index and stroke-associated pneumonia in elderly patients and factors of SAP Open
View article: Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia
Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia Open
Purpose To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features. Method…
View article: Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China
Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China Open
Introduction Stroke is a leading cause of mortality and disability worldwide. Recurrent strokes result in prolonged hospitalisation and worsened functional outcomes compared with the initial stroke. Thus, it is critical to identify patient…
View article: Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke
Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke Open
NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI can predict the occurrence of SAP. Among the indices, the NLR was the best predictor of SAP occurrence. It can therefore be used for the early identification of SAP.
View article: Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics
Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics Open
Purpose This study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS). Methods The MRI and…
View article: A 672-nW, 670-n<i>Vrms</i> ECG Acquisition AFE With Noise-Tolerant Heartbeat Detector
A 672-nW, 670-n<i>Vrms</i> ECG Acquisition AFE With Noise-Tolerant Heartbeat Detector Open
This paper presents an electrocardiogram acquisition analog front-end (AFE) with a noise tolerant heartbeat (HB) detector. Source degradation and transconductance bootstrap techniques are incorporated into the AFE to reduce the 1/f noise o…