… the experience of the decision manager. Despite using artificial intelligent techniques, the
self-explanatory structure of the decision trees together with fuzzy logic algorithms turns our …

… (CDSS) thereby providing the health professionals with … within i-DSS research is machine
learning, which allows DSS to … trees have the advantage that they are not black-box models, …

… Machine Learning (ML) algorithms in decision support. The studies relied on (n = 14) ML
algorithms … as reducing the cost of healthcare. This review found that implementing IDS with ML …

… the performances of various machine learning algorithms, we tried six different models as
listed … This study reports machine learning model that is expected to aid in the decision-making …

… machine learning models for analyzing the epidemic process; creation of a bank of simulation
models; improvement of methods of intelligent … of state power, the Public Health Centers of …

… It helps improve patient monitoring without visiting the health center [9, 10]. … disease making
use of various machine learning algorithms. Different decision support systems proposed by …

… state-of-theart machine learning models and a decision support system based on these …
machine learning, text mining, and intelligent decision support systems in the areas of healthcare…

… machine learning models’ decisions are whether we should trust these decisions and how
machine learning or deep learning models … behavior of intelligent autonomous systems to be …

… designed to assist in the delivery of healthcare, and ML is … person-specific information,
intelligently filtered, or presented … concordance rate between machine learning models and what …

… an association between the use of machine learning–based clinical algorithms to … machine
learning (ML)–based clinical decision support systems (CDSSs) are described in the medical …