A computer-aided diagnosis system for the classification of COVID-19 and non-COVID-19 pneumonia on chest X-ray images by integrating CNN with sparse …
JL Gayathri, B Abraham, MS Sujarani… - Computers in biology and …, 2022 - Elsevier
Several infectious diseases have affected the lives of many people and have caused great
dilemmas all over the world. COVID-19 was declared a pandemic caused by a newly …
dilemmas all over the world. COVID-19 was declared a pandemic caused by a newly …
EEG-based neonatal sleep stage classification using ensemble learning
Sleep stage classification can provide important information regarding neonatal brain
development and maturation. Visual annotation, using polysomnography (PSG), is …
development and maturation. Visual annotation, using polysomnography (PSG), is …
A hybrid DCNN-SVM model for classifying neonatal sleep and wake states based on facial expressions in video
Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake
pattern, which functions as an essential indicator of neurophysiological organization in the …
pattern, which functions as an essential indicator of neurophysiological organization in the …
A convolutional neural network-based decision support system for neonatal quiet sleep detection
Sleep plays an important role in neonatal brain and physical development, making its
detection and characterization important for assessing early-stage development. In this …
detection and characterization important for assessing early-stage development. In this …
Electroencephalography (EEG) based neonatal sleep staging and detection using various classification algorithms
Automatic sleep staging of neonates is essential for monitoring their brain development and
maturity of the nervous system. EEG based neonatal sleep staging provides valuable …
maturity of the nervous system. EEG based neonatal sleep staging provides valuable …
An ensemble voting approach with innovative multi-domain feature fusion for neonatal sleep stratification
A limited number of electroencephalography (EEG) channels are useful for neonatal sleep
classification, particularly in the Internet of Medical Things (IoMT) field, where compact and …
classification, particularly in the Internet of Medical Things (IoMT) field, where compact and …
Generalized camera-based infant sleep-wake monitoring in NICUs: A multi-center clinical trial
The infant sleep-wake behavior is an essential indicator of physiological and neurological
system maturity, the circadian transition of which is important for evaluating the recovery of …
system maturity, the circadian transition of which is important for evaluating the recovery of …
Fusing pre-trained convolutional neural networks features for multi-differentiated subtypes of liver cancer on histopathological images
X Dong, M Li, P Zhou, X Deng, S Li, X Zhao… - BMC Medical Informatics …, 2022 - Springer
Liver cancer is a malignant tumor with high morbidity and mortality, which has a tremendous
negative impact on human survival. However, it is a challenging task to recognize tens of …
negative impact on human survival. However, it is a challenging task to recognize tens of …
Classification of IHC images of NATs with ResNet-FRP-LSTM for predicting survival rates of rectal cancer patients
Background: Over a decade, tissues dissected adjacent to primary tumors have been
considered “normal” or healthy samples (NATs). However, NATs have recently been …
considered “normal” or healthy samples (NATs). However, NATs have recently been …
EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification
An optimal arrangement of electrodes during data collection is essential for gaining a
deeper understanding of neonatal sleep and assessing cognitive health in order to reduce …
deeper understanding of neonatal sleep and assessing cognitive health in order to reduce …