Deep learning techniques for liver and liver tumor segmentation: A review
Liver and liver tumor segmentation from 3D volumetric images has been an active research
area in the medical image processing domain for the last few decades. The existence of …
area in the medical image processing domain for the last few decades. The existence of …
Role of artificial intelligence in COVID-19 detection
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …
COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network
The reliable and rapid identification of the COVID-19 has become crucial to prevent the
rapid spread of the disease, ease lockdown restrictions and reduce pressure on public …
rapid spread of the disease, ease lockdown restrictions and reduce pressure on public …
Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks
This article presents a systematic overview of artificial intelligence (AI) and computer vision
strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized …
strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized …
Explainable deep learning model for automatic mulberry leaf disease classification
Mulberry leaves feed Bombyx mori silkworms to generate silk thread. Diseases that affect
mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the …
mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the …
[HTML][HTML] COVID-19 detection and analysis from lung CT images using novel channel boosted CNNs
In December 2019, the global pandemic COVID-19 in Wuhan, China, affected human life
and the worldwide economy. Therefore, an efficient diagnostic system is required to control …
and the worldwide economy. Therefore, an efficient diagnostic system is required to control …
Restoration of motion-corrupted EEG signals using attention-guided operational CycleGAN
Electroencephalogram (EEG) signals suffer substantially from motion artifacts even in
ambulatory settings. Signal processing techniques for removing motion artifacts from EEG …
ambulatory settings. Signal processing techniques for removing motion artifacts from EEG …
[HTML][HTML] QUCoughScope: an intelligent application to detect COVID-19 patients using cough and breath sounds
Problem—Since the outbreak of the COVID-19 pandemic, mass testing has become
essential to reduce the spread of the virus. Several recent studies suggest that a significant …
essential to reduce the spread of the virus. Several recent studies suggest that a significant …
Kidney cancer diagnosis and surgery selection by machine learning from CT scans combined with clinical metadata
Simple Summary Diagnosis is the most important step in treating and managing kidney
cancer, requiring accurate identification, localization, and classification of tumor regions. The …
cancer, requiring accurate identification, localization, and classification of tumor regions. The …
Effective hybrid deep learning model for COVID‐19 patterns identification using CT images
DA Ibrahim, DA Zebari, HJ Mohammed… - Expert …, 2022 - Wiley Online Library
Abstract Coronavirus disease 2019 (COVID‐19) has attracted significant attention of
researchers from various disciplines since the end of 2019. Although the global epidemic …
researchers from various disciplines since the end of 2019. Although the global epidemic …