Observations on the Role of Artificial Intelligence Techniques in Geographic Information Processing

1993 ◽  
pp. 85-118
Author(s):  
Dundee Navinchandra
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Geographic Information ◽  
Artificial Intelligence Techniques

scholarly journals Application of artificial intelligence in pancreaticobiliary diseases

2021 ◽  
Vol 14 ◽  
pp. 263177452199305
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Zhongheng Zhang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Response To Treatment ◽  
Endoscopic Retrograde ◽  
Artificial Intelligence Techniques ◽  
Computer Aided ◽  
Rapid Pace ◽  
Cystic Pancreatic Lesions ◽  
Aided Diagnosis

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.

AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

scholarly journals The role of artificial intelligence techniques in scheduling systems

1990 ◽  
Vol 7 (3-4) ◽  
pp. 231-242 ◽  
Author(s):  
Amy L. Geoffroy ◽  
Daniel L. Britt ◽  
John R. Gohring
Keyword(s):  
Artificial Intelligence ◽  
Artificial Intelligence Techniques

The Role of Artificial Intelligence Within the Scope of Digital Transformation in Enterprises

2020 ◽  
pp. 122-146 ◽  
Author(s):  
M. Hanefi Calp
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Digital Transformation ◽  
New Era ◽  
Artificial Intelligence Techniques ◽  
Reasoning Problem ◽  
Analytical Thinking ◽  
Effective Service

Digital transformation, which is the beginning of a new era, and performed in order to provide a more effective service, has become a compulsory situation for the enterprises that take into account the increasing corporate volumes. However, the processes and technologies used in this transformation may change according to the enterprise volume and needs. At this point, activities that implement artificial intelligence technologies will make significant contributions to digital transformation. Artificial intelligence technologies serve many purposes such as search, reasoning, problem-solving, perception, learning, estimating, analytical thinking, optimization, and planning. The purpose of this chapter is to demonstrate the effects of artificial intelligence techniques on the processes of digital transformation utilized in enterprises by considering the difficulties experienced in the realization of digital transformation. It is expected that the study will provide a perspective for other studies on digital transformation and thus create an awareness.

scholarly journals Role of Artificial Intelligence in Medicine and Clinical Research

2021 ◽  
Vol 9 (8) ◽  
pp. 1512-1518
Author(s):  
Jhumpa Sarma
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Clinical Settings ◽  
Business Sector ◽  
Process Automation ◽  
Artificial Intelligence Techniques ◽  
Fuzzy Expert Systems ◽  
Artificial Neural ◽  
Time Required

Abstract: Artificial Intelligence is a branch of computer science that enables to analyse complex medical data. The proficiency of artificial intelligence techniques has been explored to a great extent in the field of medicine. Most of the medications go to the business sector after a long tedious process of drug development. It can take a period of 10-15 years or more to convey a medication from its introductory revelation to the hands of the patients. Artificial Intelligence can significantly reduce the time required and can also cut down the expenses by half. Among the methods, artificial neural network is the most widely used analytical tool while other techniques like fuzzy expert systems, natural language processing, robotic process automation and evolutionary computation have been used in different clinical settings. The aim of this paper is to discuss the different artificial intelligence techniques and provide a perspective on the benefits, future opportunities and risks of established artificial intelligence applications in clinical practice on medical education, physicians, healthcare institutions and bioethics. Keywords: Artificial intelligence, clinical trials, medical technologies, artificial neural networks, diagnosis.

CORRELATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES WITH SOFT COMPUTING IN VARIOUS AREAS

2017 ◽  
Vol 5 (4) ◽  
pp. 58-65
Author(s):  
Avinash Kumar ◽  
Abhishek Kumar ◽  
Arun Prasad Burnwal
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Soft Computing ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Human Information Processing ◽  
Artificial Intelligence Techniques ◽  
Mathematical Techniques ◽  
Build System ◽  
Modern Era

Artificial Intelligence (AI) is a part of computer science concerned with designing intelligent computer systems that exhibit the characteristics used to associate with intelligence in human behavior. Basically, it define as a field that study and design of intelligent agents. Traditional AI approach deals with cognitive and biological models that imitate and describe human information processing skills. This processing skills help to perceive and interact with their environment. But in modern era developers can build system that assemble superior information processing needs of government and industry by choosing from large areas of mature technologies. Soft Computing (SC) is an added area of AI. It focused on the design of intelligent systems that process uncertain, imprecise and incomplete information. It applied in real world problems frequently to offer more robust, tractable and less costly solutions than those obtained by more conventional mathematical techniques. This paper reviews correlation of artificial intelligence techniques with soft computing in various areas.

Translatability of Law and Legal Technology

2020 ◽  
pp. 520-540
Author(s):  
Wolfgang Alschner ◽  
John Mark Keyes
Keyword(s):  
Artificial Intelligence ◽  
Federal Legislation ◽  
Federal Regulations ◽  
Artificial Intelligence Techniques ◽  
Tax Legislation ◽  
Legal Texts ◽  
Technology Applications ◽  
Legal Technology

Lawyers and citizens increasingly engage with law through technology intermediaries. For example, to declare their taxes, they consult tax software rather than tax legislation. This greater role of legal technology raises new issues for bilingual jurisdictions. In Canada, for instance, federal legislation is not translated but simultaneously codrafted by francophone and anglophone lawyers, resulting in small differences in the expression of the law and occasional inconsistencies. This contribution showcases how these differences can affect legal technology applications. Depending on the language they work with, lawyers may encode different interpretations in software, and algorithms may yield different results. Using a bilingual corpus of 3,000 Canadian federal regulations as a case study, the authors demonstrate that the same artificial intelligence techniques applied to the same legal texts in different languages yield different results. As a consequence, they argue that legal technology cannot simply be developed for one language and then translated to another language. Instead, it has to be “codeveloped” for different languages, similar to how legislation can be “codrafted.”

Sign in / Sign up

Export Citation Format

Share Document