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Five core crypto forecasting methods compared: technical analysis, on-chain metrics, sentiment scoring, fundamental analysis, ...

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...

Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Comprehensive 2D-GC coupled to H2S chemiluminescence enabled high-sensitivity sulfur speciation, expanding the SSFB sulfurome to 88 annotated compounds. Ensemble chemometrics and machine-learning ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, has announced a groundbreaking achievement of great theoretical and engineering significance: its ...

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...

On Friday the 20th of March 2026, M.Sc. Michael Mechenich defends his PhD thesis on Machine Learning Methods for Ecological Modeling Under Global Change. The thesis is related to research done in the ...

We provide here a R package which combine multiple Feature Selection (FS) methods in a workflow for analizing high-dimentional omics data. The different feature selection steps can be classificated in ...

ABSTRACT: This study presents a comprehensive comparative analysis of machine learning models for real-time detection of Mirai botnet attacks in IoT networks. With the proliferation of IoT devices ...