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Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning.

Neural networks : the official journal of the International Neural Network Society
Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competiti...

ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms.

Nucleic acids research
Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They have caused significant clinical burden and been responsible for a large portion of new drug development failure. Molecular understanding and in silico ...

Expected energy-based restricted Boltzmann machine for classification.

Neural networks : the official journal of the International Neural Network Society
In classification tasks, restricted Boltzmann machines (RBMs) have predominantly been used in the first stage, either as feature extractors or to provide initialization of neural networks. In this study, we propose a discriminative learning approach ...

On Equivalence of FIS and ELM for Interpretable Rule-Based Knowledge Representation.

IEEE transactions on neural networks and learning systems
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions and rules into the hidden layer of extreme learning machine (ELM). Similar to the concept of ELM that employed the random initialization technique, th...

Knowledge-guided generative artificial intelligence for automated taxonomy learning from drug labels.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To automatically construct a drug indication taxonomy from drug labels using generative Artificial Intelligence (AI) represented by the Large Language Model (LLM) GPT-4 and real-world evidence (RWE).

A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic ...

Image-based recognition of parasitoid wasps using advanced neural networks.

Invertebrate systematics
Hymenoptera has some of the highest diversity and number of individuals among insects. Many of these species potentially play key roles as food sources, pest controllers and pollinators. However, little is known about the diversity and biology and ~8...

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong.

Systematic biology
Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computation...

Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data.

Genome biology and evolution
The advent of high-throughput sequencing technologies has not only revolutionized the field of bioinformatics but has also heightened the demand for efficient taxonomic classification. Despite technological advancements, efficiently processing and an...