Visual detection of COVID-19 from materials aspect
In the recent COVID-19 pandemic, World Health Organization emphasized that early
detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses. Several …
detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses. Several …
Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey
The unpredictable pandemic came to light at the end of December 2019, known as the novel
coronavirus, also termed COVID-19, identified by the World Health Organization (WHO). The …
coronavirus, also termed COVID-19, identified by the World Health Organization (WHO). The …
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 …
Explainable COVID-19 detection using fractal dimension and vision transformer with Grad-CAM on cough sounds
The polymerase chain reaction (PCR) test is not only time-intensive but also a contact
method that puts healthcare personnel at risk. Thus, contactless and fast detection tests are …
method that puts healthcare personnel at risk. Thus, contactless and fast detection tests are …
[HTML][HTML] A novel deep learning model to detect COVID-19 based on wavelet features extracted from Mel-scale spectrogram of patients' cough and breathing sounds
M Aly, NS Alotaibi - Informatics in Medicine Unlocked, 2022 - Elsevier
The goal of this paper is to classify the various cough and breath sounds of COVID-19
artefacts in the signals from dynamic real-life environments. The main reason for choosing …
artefacts in the signals from dynamic real-life environments. The main reason for choosing …
Perovskite-based optoelectronic systems for neuromorphic computing
Brain-like neuromorphic computing system offers the ability to be used in neural networks on
demand and are rapidly gaining interest by researchers due to their outstanding …
demand and are rapidly gaining interest by researchers due to their outstanding …
Deep learning approach for early prediction of COVID-19 mortality using chest X-ray and electronic health records
SM Baik, KS Hong, DJ Park - BMC bioinformatics, 2023 - Springer
Background An artificial-intelligence (AI) model for predicting the prognosis or mortality of
coronavirus disease 2019 (COVID-19) patients will allow efficient allocation of limited …
coronavirus disease 2019 (COVID-19) patients will allow efficient allocation of limited …
Automated grading of prenatal hydronephrosis severity from segmented kidney ultrasounds using deep learning
Background and motivations Antenatal or prenatal hydronephrosis (AHN) is a common
kidney complication in unborn children. While AHN is generally benign and resolves over …
kidney complication in unborn children. While AHN is generally benign and resolves over …
A Smart Multimodal Biomedical Diagnosis Based on Patient's Medical Questions and Symptoms
V Gunturu, R Krishnamoorthy, MA Begum… - 5G-Based Smart …, 2023 - taylorfrancis.com
The exponential increase of health-related digital data has given machine learning
algorithms a newfound ability to generate more meaningful insights. Information such as …
algorithms a newfound ability to generate more meaningful insights. Information such as …
TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images
Tuberculosis (TB) is a chronic infectious lung disease, which caused the death of about 1.5
million people in 2020 alone. Therefore, it is important to detect TB accurately at an early …
million people in 2020 alone. Therefore, it is important to detect TB accurately at an early …