Yayıncı "PEERJ INC" için listeleme
Toplam kayıt 6, listelenen: 1-6
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Aguhyper: a hyperledger-based electronic health record management framework
(PEERJ INC, 2024)The increasing importance of healthcare records, particularly given the emergence of new diseases, emphasizes the need for secure electronic storage and dissemination. With these records dispersed across diverse healthcare ... -
Comparative analysis of machine learning approaches for predicting respiratory virus infection and symptom severity
(PEERJ INC, 2023)Respiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the ... -
CSA-DE-LR: enhancing cardiovascular disease diagnosis with a novel hybrid machine learning approach
(PEERJ INC, 2024)Cardiovascular diseases (CVD) are a leading cause of mortality globally, necessitating the development of efficient diagnostic tools. Machine learning (ML) and metaheuristic algorithms have become prevalent in addressing ... -
Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods
(PEERJ INC, 2022)The tremendous boost in next generation sequencing and in the “omics” technologies makes it possible to characterize the human gut microbiome—the collective genomes of the microbial community that reside in our gastrointestinal ... -
Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network
(PEERJ INC, 2024)Cyberattacks are increasingly becoming more complex, which makes intrusion detection extremely difficult. Several intrusion detection approaches have been developed in the literature and utilized to tackle computer security ... -
Topological feature generation for link prediction in biological networks
(PEERJ INC, 2023)Graph or network embedding is a powerful method for extracting missing or potential information from interactions between nodes in biological networks. Graph embedding methods learn representations of nodes and interactions ...
