The "Internet-of-Medical-Vehicles (IOMV)" is one of the special applications of the Internet of Things resulting from combining connected healthcare and connected vehicles. As the IOMV communicates with a variety of networks along its travel path, it...
Stock market forecasting is one of the most challenging problems in today's financial markets. According to the efficient market hypothesis, it is almost impossible to predict the stock market with 100% accuracy. However, Machine Learning (ML) method...
High-throughput computational platforms are being established to accelerate drug discovery. Servier launched the Patrimony platform to harness computational sciences and artificial intelligence (AI) to integrate massive multimodal data from internal ...
BACKGROUND: Clinicians' scope of responsibilities is being steadily transformed by digital health solutions that operate with or without artificial intelligence (DAI solutions). Most tools developed to foster ethical practices lack rigor and do not c...
[Formula: see text] Advances in neuroimaging, combined with developments in artificial intelligence software, have allowed researchers to noninvasively decode the brain and 'read the mind'.
A comprehensive literature review of self-balancing robot (SBR) provides an insight to the strengths and limitations of the available control techniques for different applications. Most of the researchers have not included the payload and its variati...
Plant diseases are a critical threat to the agricultural sector. Therefore, accurate plant disease classification is important. In recent years, some researchers have used synthetic images of GAN to enhance plant disease recognition accuracy. In this...
Functional connectivity (FC) refers to the statistical dependencies between activity of distinct brain areas. To study temporal fluctuations in FC within the duration of a functional magnetic resonance imaging (fMRI) scanning session, researchers hav...
I raise an ethical problem with physicians using "black box" medical AI algorithms, arguing that its use would compromise proper patient care. Even if AI results are reliable, my contention is that without being able to explain medical decisions to p...
OBJECTIVE: Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple data sources without directly sharing data. Due to the large amount of sensitive data in dentistry, FL may be particularly relevant...
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