Scientists’ Side Hustle? Using AI and Quantum Computing to Generate New Peptides

Researchers cobbled together funding and time to show how quantum computing could aid in the development of drugs to help ...
IEEE

Machine Learning-Driven Ontological Knowledge Base for Bridge Corrosion Evaluation

Abstract: In bridge maintenance, assessing structural performance requires adherence to rules outlined in safety and regulatory standards which can be effectively and formally represented in both ...
BMJ

Phenotypes of non-alcoholic fatty liver disease (NAFLD) and all-cause mortality: unsupervised machine learning analysis of NHANES III

Objectives Non-alcoholic fatty liver disease (NAFLD) is a non-communicable disease with a rising prevalence worldwide and with large burden for patients and health systems. To date, the presence of ...
Frontiers

From clinical phenotypes to genomic signatures: machine learning integration for precision tuberculosis treatment prediction

Tuberculosis (TB) remains a major global health threat, causing approximately 1.5 million deaths each year. Despite progress in treatment, 15%–20% of patients still experience treatment failure or ...
Frontiers

Protecting digital assets using an ontology based cyber situational awareness system

Cyber situational awareness is critical for detecting and mitigating cybersecurity threats in real-time. This study introduces a comprehensive methodology that integrates the Isolation Forest and ...
Scientific Research Publishing

Cimiano, P. (2006) Ontology Learning and Population from Text: Algorithms, Evaluation and Applications (Vol. 27). Springer Science & Business Media, Berlin.

ABSTRACT: With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with ...