Applications of AI‐Enabled Analytics

2022 ◽  
pp. 39-55
Keyword(s):  
Applications Of Ai

Sports Medicine and Artificial Intelligence: A Primer

2021 ◽  
pp. 036354652110086
Author(s):  
Prem N. Ramkumar ◽  
Bryan C. Luu ◽  
Heather S. Haeberle ◽  
Jaret M. Karnuta ◽  
Benedict U. Nwachukwu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sports Medicine ◽  
Injury Risk ◽  
Industrial Revolution ◽  
Improve Patient Care ◽  
Great Promise ◽  
Patient Reported ◽  
Athlete Injury ◽  
Improve Patient ◽  
Applications Of Ai

Artificial intelligence (AI) represents the fourth industrial revolution and the next frontier in medicine poised to transform the field of orthopaedics and sports medicine, though widespread understanding of the fundamental principles and adoption of applications remain nascent. Recent research efforts into implementation of AI in the field of orthopaedic surgery and sports medicine have demonstrated great promise in predicting athlete injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting the patient experience. Not unlike the recent emphasis thrust upon physicians to understand the business of medicine, the future practice of sports medicine specialists will require a fundamental working knowledge of the strengths, limitations, and applications of AI-based tools. With appreciation, caution, and experience applying AI to sports medicine, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. In this Current Concepts review, we discuss the definitions, strengths, limitations, and applications of AI from the current literature as it relates to orthopaedic sports medicine.

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

Welcome to AI Matters 7(1)

AI Matters ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 4-4
Author(s):  
Iolanda Leite ◽  
Anuj Karpatne
Keyword(s):  
High School Students ◽  
Regular Education ◽  
Physical World ◽  
School Students ◽  
Social Good ◽  
The Third ◽  
Ai Ethics ◽  
K 12 ◽  
Applications Of Ai

Welcome to the first issue of this year's AI Matters Newsletter! We start with a report on upcoming SIGAI Events by Dilini Samarasinghe and Conference reports by Louise Dennis, our conference coordination officers. In our regular Education column, Duri Long, Jonathan Moon, and Brian Magerko introduce two "unplugged" activities (i.e., no technology needed) to learn about AI focussed on K-12 AI Education. We then bring you our regular Policy column, where Larry Medsker covers several topics on AI policy, including the role of Big Tech on AI Ethics and an interview with Dr. Eric Daimler who is the CEO of the MIT-spinout Conexus.com. Finally, we close with four article contributions. The first article discusses emerging applications of AI in analyzing source code and its implications to several industries. The second article discusses topics in the area of physical scene understanding that are necessary for machines to perceive, interact, and reason about the physical world. The third article presents novel practices and highlights from the Fourth Workshop on Mechanism Design for Social Good. The fourth article provides a report on the "Decoding AI" event that was conducted online by ViSER for high school students and adults sponsored by ACM SIGAI.

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence

2020 ◽  
Vol 24 (01) ◽  
pp. 38-49 ◽  
Author(s):  
Natalia Gorelik ◽  
Jaron Chong ◽  
Dana J. Lin
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Bone Tumors ◽  
Image Interpretation ◽  
Bone Age ◽  
Musculoskeletal Imaging ◽  
Radiology Workflow ◽  
Disease Response ◽  
Osseous Metastases ◽  
Applications Of Ai

AbstractArtificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect and characterize abnormalities as well as monitor disease response. Many AI-based image interpretation tasks for musculoskeletal (MSK) pathologies have been studied, including the diagnosis of bone tumors, detection of osseous metastases, assessment of bone age, identification of fractures, and detection and grading of osteoarthritis. This article explores the applications of AI for image interpretation of MSK pathologies.

Appreciative inquiry's potential in program evaluation and research

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dana M. Griggs ◽  
Mindy Crain-Dorough
Keyword(s):  
Program Evaluation ◽  
Public Education ◽  
Research Study ◽  
Design Stage ◽  
Research Approach ◽  
Evaluation Tool ◽  
Content Type ◽  
Educational Partnership ◽  
Data Saturation ◽  
Applications Of Ai

PurposeThe purposes of this paper are to provide a description of AI and to document and compare two applications of AI, one in program evaluation and another in an applied research study.Design/methodology/approachFocus groups, interviews and observations were used to gather rich qualitative data which was used to detail Appreciative Inquiry's value in evaluation and research.FindingsAI aided the researcher in connecting with the participants and valuing what they shared. In both studies, the use of AI amassed information that answered the research questions, provided a rich description of the context and findings, and led to data saturation. The authors describe and compare experiences with two applications of AI: program evaluation and a research study. This paper contributes further understanding of the use of AI in public education institutions. The researchers also explore the efficacy of using AI in qualitative research and recommend its use for multiple purposes.Research limitations/implicationsLimitations occurred in the AI-Design Stage by using a positive viewpoint and because both program and partnership studied were new with limited data to use for designing a better future. So, the authors recommend a revisit of both studies through the same 4D Model.Practical implicationsThis manuscript shows that AI is useful for evaluation and research. It amplifies the participants' voices through favorite stories and successes. AI has many undiscovered uses.Social implicationsThrough the use of AI the authors can: improve theoretical perspectives; conduct research that yields more authentic data; enable participants to deeply reflect on their practice and feel empowered; and ultimately impact and improve the world.Originality/valueAI is presented as an evaluation tool for a high-school program and as a research approach identifying strengths and perceptions of an educational partnership. In both studies, AI crumbled the walls that are often erected by interviewees when expecting to justify or defend decisions and actions. This paper contributes further understanding of the use of AI in public education institutions.

Legal challenges in bringing AI evidence to the criminal courtroom

2021 ◽  
pp. 203228442110570
Author(s):  
Katherine Quezada-Tavárez ◽  
Plixavra Vogiatzoglou ◽  
Sofie Royer
Keyword(s):  
Criminal Justice ◽  
Criminal Law ◽  
Justice System ◽  
Case Law ◽  
Fair Trial ◽  
Criminal Proceedings ◽  
Legal Challenges ◽  
Criminal Courtroom ◽  
European Criminal Law ◽  
Applications Of Ai

Artificial Intelligence (AI) is rapidly transforming the criminal justice system. One of the promising applications of AI in this field is the gathering and processing of evidence to investigate and prosecute crime. Despite its great potential, AI evidence also generates novel challenges to the requirements in the European criminal law landscape. This study aims to contribute to the burgeoning body of work on AI in criminal justice, elaborating upon an issue that has not received sufficient attention: the challenges triggered by AI evidence in criminal proceedings. The analysis is based on the norms and standards for evidence and fair trial, which are fleshed out in a large amount of European case law. Through the lens of AI evidence, this contribution aims to reflect on these issues and offer new perspectives, providing recommendations that would help address the identified concerns and ensure that the fair trial standards are effectively respected in the criminal courtroom.

Applications of AI in Financial System

2017 ◽  
pp. 101-109
Author(s):  
Santosh Kumar ◽  
Roopali Sharma
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Decision Analysis ◽  
Computer Science ◽  
Investment Decision ◽  
Analysis Tool ◽  
Changing Environment ◽  
Human Interference ◽  
Applications Of Ai

Role of computers are widely accepted and well known in the domain of Finance. Artificial Intelligence(AI) methods are extensively used in field of computer science for providing solution of unpredictable event in a frequent changing environment with utilization of neural network. Professionals are using AI framework into every field for reducing human interference to get better result from few decades. The main objective of the chapter is to point out the techniques of AI utilized in field of finance in broader perspective. The purpose of this chapter is to analyze the background of AI in finance and its role in Finance Market mainly as investment decision analysis tool.

Is AI in Your Future?

2021 ◽  
pp. 101-117
Author(s):  
Darrell Wayne Gunter
Keyword(s):  
Human Beings ◽  
Introduction History ◽  
Vannevar Bush ◽  
John Mccarthy ◽  
Applications Of Ai

AI was first coined by John McCarthy in 1956. Vannevar Bush penned an article, “As We Make Think,” that was first published in The Atlantic, and five years later, Alan Turning wrote a paper on the notion of machines being able to simulate human beings. AI had a number of significant contributors, which this chapter chronicles along with the definitions and their achievements. This chapter will provide an introduction, history, and overview of AI. It will also provide examples of the four waves of AI and the current applications and future applications of AI.

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