Merits of Bayesian networks in overcoming small data challenges: A meta-model for handling missing data
The abundant availability of data in Big Data era has helped achieving significant advances
in the machine learning field. However, many datasets appear with incompleteness from …
in the machine learning field. However, many datasets appear with incompleteness from …
AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach
Background Automated coaches (eCoach) can help people lead a healthy lifestyle (eg,
reduction of sedentary bouts) with continuous health status monitoring and personalized …
reduction of sedentary bouts) with continuous health status monitoring and personalized …
Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques
Background Sub-Saharan Africa faces high neonatal and maternal mortality rates due to
limited access to skilled healthcare during delivery. This study aims to improve the …
limited access to skilled healthcare during delivery. This study aims to improve the …
Forecasting Survival Rates in Metastatic Colorectal Cancer Patients Undergoing Bevacizumab-Based Chemotherapy: A Machine Learning Approach
Background: Antibiotics can play a pivotal role in the treatment of colorectal cancer (CRC) at
various stages of the disease, both directly and indirectly. Identifying novel patterns of …
various stages of the disease, both directly and indirectly. Identifying novel patterns of …
Detection of Non-Technical Losses on a Smart Distribution Grid Based on Artificial Intelligence Models
MA Souza, HTV Gouveia, AA Ferreira… - Energies, 2024 - mdpi.com
Non-technical losses (NTL) have been a growing problem over the years, causing
significant financial losses for electric utilities. Among the methods for detecting this type of …
significant financial losses for electric utilities. Among the methods for detecting this type of …