The potential role of artificial intelligence/expert systems in the warning and forecast operations of the National Weather Service

1986 ◽  
Author(s):  
I. RACER ◽  
J. GAFFNEY, JR.
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Potential Role ◽  
National Weather Service ◽  
Weather Service

scholarly journals The Interplay of Knowledge Representation with Various Fields of Artificial Intelligence in Medicine

2019 ◽  
Vol 28 (01) ◽  
pp. 027-034 ◽  
Author(s):  
Laszlo Balkanyi ◽  
Ronald Cornet
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Knowledge Representation ◽  
Expert Systems ◽  
Frequency Analysis ◽  
Medical Subject Headings ◽  
Subject Headings

Introduction: Artificial intelligence (AI) is widespread in many areas, including medicine. However, it is unclear what exactly AI encompasses. This paper aims to provide an improved understanding of medical AI and its constituent fields, and their interplay with knowledge representation (KR). Methods: We followed a Wittgensteinian approach (“meaning by usage”) applied to content metadata labels, using the Medical Subject Headings (MeSH) thesaurus to classify the field. To understand and characterize medical AI and the role of KR, we analyzed: (1) the proportion of papers in MEDLINE related to KR and various AI fields; (2) the interplay among KR and AI fields and overlaps among the AI fields; (3) interconnectedness of fields; and (4) phrase frequency and collocation based on a corpus of abstracts. Results: Data from over eighty thousand papers showed a steep, six-fold surge in the last 30 years. This growth happened in an escalating and cascading way. A corpus of 246,308 total words containing 21,842 unique words showed several hundred occurrences of notions such as robotics, fuzzy logic, neural networks, machine learning and expert systems in the phrase frequency analysis. Collocation analysis shows that fuzzy logic seems to be the most often collocated notion. Neural networks and machine learning are also used in the conceptual neighborhood of KR. Robotics is more isolated. Conclusions: Authors note an escalation of published AI studies in medicine. Knowledge representation is one of the smaller areas, but also the most interconnected, and provides a common cognitive layer for other areas.

scholarly journals Android Based Expert System Application for Diagnose COVID-19 Disease: Cases Study of Banyumas Regency

2020 ◽  
Vol 1 (2) ◽  
pp. 26
Author(s):  
Rosyid Ridlo Al Hakim ◽  
Erfan Rusdi ◽  
Muhammad Akbar Setiawan
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Confidence Level ◽  
Certainty Factor ◽  
Global Pandemic ◽  
Android Os ◽  
The Status

Since being confirmed by WHO, the status of COVID-19 outbreak has become a global pandemic, the number of cases has been confirmed positive, cured, and even death worldwide. Artificial intelligence in the medical has given rise to expert systems that can replace the role of experts (doctors). Tools to detect someone affected by COVID-19 have not been widely applied in all regions. Banyumas Regency, Indonesia is included confirmed region of COVID-19 cases, and it’s difficult for someone to know the symptoms that are felt whether these symptoms include indications of someone ODP, PDP, positive, or negative COVID-19, and still at least a referral hospital handling COVID-19. Expert system with certainty factor can help someone make a self-diagnose whether including ODP, PDP, positive, or negative COVID-19. This expert system provides ODP diagnostic results with a confidence level of 99.96%, PDP 99.99790%, positive 99.9999997%, negative 99.760384%, and the application runs well on Android OS

Artificial Intelligence and Its Implications in Education

2021 ◽  
pp. 222-235
Author(s):  
Uttam Sharma ◽  
Pradeep Tomar ◽  
Harshit Bhardwaj ◽  
Aditi Sakalle
Keyword(s):  
Artificial Intelligence ◽  
Speech Recognition ◽  
Visual Perception ◽  
Expert Systems ◽  
Learning Environments ◽  
Market Size ◽  
Life Outcomes ◽  
Tutoring Systems ◽  
To Come

Computer equipment, software, and online service have succeeded in introducing improvements and enhancements to the classrooms and teaching methods in recent years. Yet, using artificial intelligence (AI), the real disruption of education has to come. Artificial intelligence has proven its position as a game-changing force in various fields, in the past causing unprecedented transformations. Using AI, expert systems can be programmed to communicate with the environment through technologies such as visual perception, speech recognition, and intellectual behavior, which we can find to be inherently human. This chapter aims to discuss the role of artificial intelligence in the education sector including its market size, the effect of AI in education, case studies of current AI presence in education (smart content, smart tutoring systems, virtual facilitators, and learning environments, etc.) to improve learning and life outcomes for all. Finally, chapter concludes with the issues and problems.

scholarly journals Bayesian Reasoning and Artificial Intelligence against COVID-19

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Michael Gr. Voskoglou ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Artificial Intelligence ◽  
World Economy ◽  
Potential Role ◽  
Reproduction Number ◽  
Case Based Reasoning ◽  
Bayesian Reasoning ◽  
The Novel ◽  
The World ◽  
Novel Coronavirus

The article focuses on the potential role of Probability Theory and Artificial Intelligence in the battle against the pandemic of COVID-19, which, starting from China on December 2019, has created a chaos in the world economy and the lives of people, causing hundreds of thousands of deaths until now. After discussing the importance of the reproduction number Ro of the viruses, the Bayesian Probabilities are used for measuring the creditability of the diagnostic tests for the novel coronavirus. Artificial Intelligence designs are also described which are used as tools against COVID-19 and a Case-Based Reasoning expert system is proposed for the COVID-19 diagnosis.

scholarly journals The Potential of Artificial Intelligence, Machine Learning, and Novel Analytic Methods to Promote Successful Aging

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 655-655
Author(s):  
Walter Boot
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Older Adults ◽  
Autonomous Vehicles ◽  
Successful Aging ◽  
Potential Role ◽  
Gerontological Society ◽  
Analytic Methods ◽  
Applications Of Ai

Abstract The Gerontological Society of America is celebrating its75th anniversary and in those75 years the world has undergone an amazing technological revolution. During this period, computers transformed from systems that once filled entire rooms to much more powerful devices that fit in our pockets. We have seen the introduction of wireless technologies, augmented and virtual reality, smart home devices, autonomous vehicles, and much more. This session focuses on a new technological advance that has the potential to support the health, wellbeing, and independence of older adults and caregivers: artificial intelligence (AI). This session will present applications of AI, Machine Learning (ML), and other novel analytic methods and how they have the potential to impact the lives of older adults in a variety of context. As AI is increasingly being involved in workplace hiring, the first talk focuses on older adults’ attitudes toward the role of AI in this decision making process. Next, novel ML approaches applied to social media are discussed in terms of understanding the needs of Alzheimer’s caregivers. Next, ML techniques are discussed in terms of developing biomarkers that can be applied in diagnosis and assessment of therapeutic responses by detecting mood, which may have important implications for older adults living with dementia. Then, the potential role of AI is discussed in terms of developing reminder systems to promote older adults’ adherence to technology-based health activities. Finally, novel analytic approaches are discussed in terms of harnessing digital metrics to detect the risk of cognitive decline.

scholarly journals Role of Artificial Intelligence in Fighting Antimicrobial Resistance in Pediatrics

Antibiotics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 767 ◽  
Author(s):  
Umberto Fanelli ◽  
Marco Pappalardo ◽  
Vincenzo Chinè ◽  
Pierpacifico Gismondi ◽  
Cosimo Neglia ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Antimicrobial Resistance ◽  
Antimicrobial Stewardship ◽  
Potential Role ◽  
Antimicrobial Agents ◽  
Primary Role ◽  
Science And Engineering ◽  
Intelligent Behavior ◽  
Applications Of Ai

Artificial intelligence (AI) is a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behavior. AI is extremely useful in many human activities including medicine. The aim of our narrative review is to show the potential role of AI in fighting antimicrobial resistance in pediatric patients. We searched for PubMed articles published from April 2010 to April 2020 containing the keywords “artificial intelligence”, “machine learning”, “antimicrobial resistance”, “antimicrobial stewardship”, “pediatric”, and “children”, and we described the different strategies for the application of AI in these fields. Literature analysis showed that the applications of AI in health care are potentially endless, contributing to a reduction in the development time of new antimicrobial agents, greater diagnostic and therapeutic appropriateness, and, simultaneously, a reduction in costs. Most of the proposed AI solutions for medicine are not intended to replace the doctor’s opinion or expertise, but to provide a useful tool for easing their work. Considering pediatric infectious diseases, AI could play a primary role in fighting antibiotic resistance. In the pediatric field, a greater willingness to invest in this field could help antimicrobial stewardship reach levels of effectiveness that were unthinkable a few years ago.

scholarly journals Potential Role of Artificial Intelligence for the Previous Study Using Traditional Analysis

2021 ◽  
Vol 13 (7) ◽  
pp. 409-411
Author(s):  
Kei Nakajima ◽  
Manami Igata ◽  
Ryoko Higuchi
Keyword(s):  
Artificial Intelligence ◽  
Potential Role

Potential Role of Artificial Intelligence in Cardiac Magnetic Resonance Imaging

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Riccardo Cau ◽  
Valeria Cherchi ◽  
Giulio Micheletti ◽  
Michele Porcu ◽  
Lorenzo Mannelli ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Artificial Intelligence ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cardiac Magnetic Resonance Imaging ◽  
Potential Role ◽  
Resonance Imaging
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