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Automatic detection of cognitive impairment in elderly people using an entertainment chatbot with Natural Language Proce...

Published in Journal of ambient intelligence and humanized computing

Previous researchers have proposed intelligent systems for therapeutic monitoring of cognitive impairments. However, most existing practical approaches for this purpose are based on manual tests. This raises issues such as excessive caretaking effort and the white-coat effect. To avoid these issues, we present an intelligent conversational system f...

New theoretical ISM-K2 Bayesian network model for evaluating vaccination effectiveness.

Published in Journal of ambient intelligence and humanized computing

Aiming at the difficulty in obtaining a complete Bayesian network (BN) structure directly through search-scoring algorithms, authors attempted to incorporate expert judgment and historical data to construct an interpretive structural model with an ISM-K2 algorithm for evaluating vaccination effectiveness (VE). By analyzing the influenza vaccine dat...

Omicron virus emotions understanding system based on deep learning architecture

Published in Journal of Ambient Intelligence and Humanized Computing

Emotions understanding has acquired a significant interest in the last few years because it has introduced remarkable services in many aspects regarding public opinion mining and recognition in the field of marketing, seeking product reviews, reviews of movies, and healthcare issues based on sentiment understanding. This conducted research has util...

Deep learning methods for biomedical information analysis

Published in Journal of Ambient Intelligence and Humanized Computing

A model to improve user acceptance of e-services in healthcare systems based on technology acceptance model: an empirica...

Published in Journal of Ambient Intelligence and Humanized Computing

Improving the quality of electronic services (e-services) is essential when dealing with unforeseen factors and uncertainties in healthcare, such as the outbreak of coronavirus (COVID-19) and changes in the needs and expectations of patients. This paper presents a comprehensive conceptual model in healthcare systems for improving the user acceptanc...

The role of explainable Artificial Intelligence in high-stakes decision-making systems: a systematic review

Published in Journal of Ambient Intelligence and Humanized Computing

A high-stakes event is an extreme risk with a low probability of occurring, but severe consequences (e.g., life-threatening conditions or economic collapse). The accompanying lack of information is a source of high-stress pressure and anxiety for emergency medical services authorities. Deciding on the best proactive plan and action in this environm...

Flu-Net: two-stream deep heterogeneous network to detect flu like symptoms from videos using grey wolf optimization algo...

Published in Journal of Ambient Intelligence and Humanized Computing

The outbreak of COVID-19 (also known as Coronavirus) has put the entire world at risk. The disease first appears in Wuhan, China, and later spread to other countries, taking a form of a pandemic. In this paper, we try to build an artificial intelligence (AI) powered framework called Flu-Net to identify flu-like symptoms (which is also an important ...

Real-time updating of dynamic social networks for COVID-19 vaccination strategies

Published in Journal of Ambient Intelligence and Humanized Computing

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be avail...