Artificial intelligence (AI)-based systems have achieved significant success in healthcare since 2016, and AI models accomplished medical tasks, at or above the performance levels of humans. Despite these achievements, various challenges exist application healthcare. One main is safety, which related to unsafe incorrect actions recommendations by algorithms. In response need address safety challenges, this research aimed develop a controlling system (SCS) framework reduce risk potential...

The COVID-19 pandemic has had unprecedented social and economic consequences in the United States. Therefore, accurately predicting dynamics of can be very beneficial. Two main elements required for developing reliable predictions include: (1) a predictive model (2) an indicator current condition status pandemic. As indicator, we used effective reproduction number (Rt), which is defined as new infections transmitted by single contagious individual population that may no longer fully...

The performance of text classification methods has improved greatly over the last decade for instances less than 512 tokens. This limit been adopted by most state-of-the-research transformer models due to high computational cost analyzing longer instances. To mitigate this problem and improve texts, researchers have sought resolve underlying causes proposed optimizations attention mechanism, which is key element every model. In our study, we are not pursuing ultimate goal long...

In December 2019, China announced the breakout of a new virus identified as coronavirus SARS-CoV-2 (COVID-19), which soon grew exponentially and resulted in global pandemic. Despite strict actions to mitigate spread various countries, COVID-19 significant loss human life 2020 early 2021. To better understand dynamics COVID-19, evidence its chaotic behavior US globally was evaluated. A 0-1 test used analyze time-series data confirmed daily cases from 1/22/2020 12/13/2020. The results show...

The COVID-19 pandemic has changed our lifestyles, habits, and daily routine. Some of the impacts have been widely reported already. However, many effects are still to be discovered. main objective this study was assess changes in frequency physical back pain complaints during pandemic. In contrast other published studies, we target general population using Twitter as a data source. Specifically, aim investigate differences number between pre-pandemic A total 53,234 78,559 tweets were...

Optimizing COVID-19 vaccine distribution can help plan around the limited production and of vaccination, particularly in early stages. One main criteria for equitable is predicting geographic active virus at time vaccination. This research developed sequence-learning models to predict behavior pandemic across US, based on previously reported information. For this objective, we used two time-series datasets confirmed cases effective reproduction numbers from January 22, 2020 November 26, all...

Coronavirus disease 2019 (COVID-19) was first discovered in China; within several months, it spread worldwide and became a pandemic. Although the virus has throughout globe, its effects have differed. The pandemic diffusion network dynamics (PDND) approach proposed to better understand spreading behavior of COVID-19 US Japan. We used daily confirmed cases from 5 January 2020 31 July 2021, for all states (prefectures) By applying time series data, we developed graphs In these graphs, nodes...

The identification of human behavior can provide useful information across multiple job spectra. Recent advances in applying data-based approaches to social sciences have increased the feasibility modeling behavior. In particular, studying by analyzing unstructured textual data has recently received considerable attention because abundance data. main objective present study was discuss primary methods for identifying and predicting through mining Of 823 articles analyzed, 87 met predefined...

The goal of this study was to conduct a literature review current approaches and techniques for identifying, understanding, predicting human behaviors through mining variety sources textual data with focus on enabling classification psychological regarding emotion, cognition, social empathy. This performed using keyword searches in ISI Web Science, Engineering Village Compendex, ProQuest Dissertations, Google Scholar. Our findings show that, despite recent advancements based unstructured...

In response to the need address safety challenges in use of artificial intelligence (AI), this research aimed develop a framework for controlling system (SCS) AI black-box mystery healthcare industry. The main objective was propose guidelines implementing models reduce risk potential healthcare-related incidents and accidents. developed by adopting multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights developing rating...

Artificial intelligence (AI) has been used to advance different fields, such as education, healthcare, and finance. However, the application of AI in field project management (PM) not progressed equally. This paper reports on a systematic review published studies investigate PM. identified relevant papers using Web Science, Science Direct, Google Scholar databases. Of 652 articles found, 58 met predefined criteria were included review. Included classified per following dimensions: PM...

In December 2019, China reported a new virus identified as SARS-CoV-2, causing COVID-19, which soon spread to other countries and led global pandemic. Although many imposed strict actions control the of virus, COVID-19 pandemic resulted in unprecedented economic social consequences 2020 early 2021. To understand dynamics we evaluated its chaotic behavior Japan. A 0–1 test was applied time-series data daily cases from January 26, August 5, 2021 (3 days before end Tokyo Olympic Games)....

The quality of text classification has greatly improved with the introduction deep learning, and more recently, models using attention mechanism. However, to address problem classifying instances that are longer than length limit adopted by most best performing transformer models, common method is naively truncate so it meets model limit. Researchers have proposed other approaches, but they do not appear be popular, because their high computational cost implementation complexity. Recently,...

In response to the need address safety challenges in use of artificial intelligence (AI), this research aimed develop a framework for controlling system (SCS) solve AI black-box mystery healthcare industry. The was developed by adopting multi-attribute value model approach (MAVT), which comprises four parts: extracting attributes, generating weights developing rating scale, and finalizing system. On basis MAVT approach, three layers attributes were created. first level contained 6 key...