Buscar
Mostrando ítems 61-70 de 108
Fast deep autoencoder for federated learning
(Elsevier Ltd, 2023-11)
[Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ...
Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques
(PeerJ, Ltd., 2020-07-27)
[Abstract]
Food consumption patterns have undergone changes that in recent years have resulted in serious health problems. Studies based on the evaluation of the nutritional status have determined that the adoption of a ...
IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection
(MDPI, 2021)
[Abstract] With advancements in engineering and science, the application of smart systems is increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT restricted power and computing ...
IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds
(MDPI, 2021)
[Abstract] The parasite species of genus Plasmodium causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, ...
Machine Learning-Based Radon Monitoring System
(MDPI, 2022)
[Abstract] Radon (Rn) is a biological threat to cells due to its radioactivity. It is capable of penetrating the human body and damaging cellular DNA, causing mutations and interfering with cellular dynamics. Human exposure ...
On a Neural Network to Extract Implied Information from American Options
(Routledge, 2022)
[Abstract] Extracting implied information, like volatility and dividend, from observed option prices is a challenging task when dealing with American options, because of the complex-shaped early-exercise regions and the ...
Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models
(Elsevier, 2023-07)
[Abstract]: COVID-19 is a global threat for the healthcare systems due to the rapid spread of the pathogen that causes it.
In such situation, the clinicians must take important decisions, in an environment where medical ...
A One-Class Classification method based on Expanded Non-Convex Hulls
(Elsevier, 2023)
[Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ...
Artificial intelligence in paediatrics: Current events and challenges
(Elsevier, 2024-03)
[Abstract]: This article examines the use of artificial intelligence (AI) in the field of paediatric care within the framework of the 7P medicine model (Predictive, Preventive, Personalized, Precise, Participatory, Peripheral ...
Machine learning analysis of TCGA cancer data
(PeerJ Inc., 2021)
[Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas ...