OBJECTIVES: This study aimed to develop five different supervised machine learning (ML) classifier models using artificial intelligence (AI) techniques and to compare their performance for cervical vertebral maturation (CVM) analysis. A clinical deci...
Ecotoxicology and environmental safety
Mar 9, 2020
Environment pollutants, especially those from total petroleum hydrocarbons (TPH), have a highly complex chemical, biological and physical impact on soils. Here we study this influence via modelling the TPH acute phytotoxicity effects on eleven sample...
This article presents the novel Python, C# and JavaScript libraries of Node Primitives (NEP), a high-level, open, distributed, and component-based framework designed to enable easy development of cross-platform software architectures. NEP is built on...
The aim of eXplainable Artificial Intelligence (XAI) is to design intelligent systems that can explain their predictions or recommendations to humans. Such systems are particularly desirable for therapeutic decision support, because physicians need t...
Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and artificial intelligence, the paradigm of biomarker discovery is shifting from traditional experimenta...
The processes and mechanisms of human learning are central to inquiries in a number of fields including psychology, cognitive science, development, education, and artificial intelligence. Arguments, debates, and controversies linger over the question...
BACKGROUND: Previous research suggests that artificial agents may be a promising source of social support for humans. However, the bulk of this research has been conducted in the context of social support interventions that specifically address stres...
Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently and more effectively than conventional methods through detection of hidden patterns within large data sets. With this in mind, there are several areas wi...
Explainable AI aims at building intelligent systems that are able to provide a clear, and human understandable, justification of their decisions. This holds for both rule-based and data-driven methods. In management of chronic diseases, the users of ...
BACKGROUND: Estimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI...
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