The future of otology

2019 ◽  
Vol 133 (09) ◽  
pp. 747-758 ◽  
Author(s):  
R K Jackler ◽  
T A Jan
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Organ Of Corti ◽  
Clinical Impact ◽  
Surgical Practice ◽  
Renaissance Period ◽  
The Future ◽  
Recent Developments ◽  
Consumer Device ◽  
Potential Clinical Impact

AbstractBackgroundThe field of otology is increasingly at the forefront of innovation in science and medicine. The inner ear, one of the most challenging systems to study, has been rendered much more open to inquiry by recent developments in research methodology. Promising advances of potential clinical impact have occurred in recent years in biological fields such as auditory genetics, ototoxic chemoprevention and organ of Corti regeneration. The interface of the ear with digital technology to remediate hearing loss, or as a consumer device within an intelligent ecosystem of connected devices, is receiving enormous creative energy. Automation and artificial intelligence can enhance otological medical and surgical practice. Otology is poised to enter a new renaissance period, in which many previously untreatable ear diseases will yield to newly introduced therapies.ObjectiveThis paper speculates on the direction otology will take in the coming decades.ConclusionMaking predictions about the future of otology is a risky endeavour. If the predictions are found wanting, it will likely be because of unforeseen revolutionary methods.

scholarly journals Artificial Intelligence for Microscopy: What You Should Know

2019 ◽  
Author(s):  
Lucas von Chamier ◽  
Romain F. Laine ◽  
Ricardo Henriques
Keyword(s):  
Artificial Intelligence ◽  
Image Segmentation ◽  
Deep Learning ◽  
Information Content ◽  
Biomedical Research ◽  
Cell Biology ◽  
Future Directions ◽  
New Horizons ◽  
The Future ◽  
Recent Developments

Artificial Intelligence based on Deep Learning is opening new horizons in Biomedical research and promises to revolutionize the Microscopy field. Slowly, it now transitions from the hands of experts in Computer Sciences to researchers in Cell Biology. Here, we introduce recent developments in Deep Learning applied to Microscopy, in a manner accessible to non-experts. We overview its concepts, capabilities and limitations, presenting applications in image segmentation, classification and restoration. We discuss how Deep Learning shows an outstanding potential to push the limits of Microscopy, enhancing resolution, signal and information content in acquired data. Its pitfalls are carefully discussed, as well as the future directions expected in this field.

scholarly journals Don't Trust Your Eyes: Image Manipulation in the Age of DeepFakes

2021 ◽  
Vol 6 ◽  
Author(s):  
Johannes Langguth ◽  
Konstantin Pogorelov ◽  
Stefan Brenner ◽  
Petra Filkuková ◽  
Daniel Thilo Schroeder
Keyword(s):  
Artificial Intelligence ◽  
Image Manipulation ◽  
The Political ◽  
Fake News ◽  
Novel Technology ◽  
Political Impact ◽  
The Future ◽  
Recent Developments ◽  
Video Material

We review the phenomenon of deepfakes, a novel technology enabling inexpensive manipulation of video material through the use of artificial intelligence, in the context of today’s wider discussion on fake news. We discuss the foundation as well as recent developments of the technology, as well as the differences from earlier manipulation techniques and investigate technical countermeasures. While the threat of deepfake videos with substantial political impact has been widely discussed in recent years, so far, the political impact of the technology has been limited. We investigate reasons for this and extrapolate the types of deepfake videos we are likely to see in the future.

scholarly journals Artificial intelligence for microscopy: what you should know

2019 ◽  
Vol 47 (4) ◽  
pp. 1029-1040 ◽  
Author(s):  
Lucas von Chamier ◽  
Romain F. Laine ◽  
Ricardo Henriques
Keyword(s):  
Artificial Intelligence ◽  
Image Segmentation ◽  
Deep Learning ◽  
Information Content ◽  
Biomedical Research ◽  
Future Directions ◽  
New Horizons ◽  
The Future ◽  
Recent Developments

Abstract Artificial Intelligence based on Deep Learning (DL) is opening new horizons in biomedical research and promises to revolutionize the microscopy field. It is now transitioning from the hands of experts in computer sciences to biomedical researchers. Here, we introduce recent developments in DL applied to microscopy, in a manner accessible to non-experts. We give an overview of its concepts, capabilities and limitations, presenting applications in image segmentation, classification and restoration. We discuss how DL shows an outstanding potential to push the limits of microscopy, enhancing resolution, signal and information content in acquired data. Its pitfalls are discussed, along with the future directions expected in this field.

Ready, Set, Code!

2020 ◽  
Author(s):  
Heather Catchpole ◽  
Nicola O’Brien
Keyword(s):  
Artificial Intelligence ◽  
Citizen Science ◽  
Programming Language ◽  
Digital Technology ◽  
Cutting Edge ◽  
Digital Art ◽  
Science Project ◽  
Hands On ◽  
The Future ◽  
Citizen Science Project

Are you ready to learn about real technology and make it yourself? Ready, Set, Code! explains how cutting-edge digital technology works and its surprising uses now and in the future. Filled with interesting examples, each chapter explores a different topic, such as artificial intelligence, sensors and data, and applies it with a fun, hands-on coding project. You will learn how to create your own chatbot, translate messages into different languages, construct a burglar alarm, make digital art and music, and launch a citizen science project. Plus, you’ll learn how to protect yourself online and much more. Suitable for beginners, this book provides illustrated step-by-step instructions to teach kids to code with the highly acclaimed Scratch programming language, popular micro:bit mini computers and simple app building tools.

Editorial for the Special Section on Humans, Algorithms, and Augmented Intelligence: The Future of Work, Organizations, and Society

2021 ◽  
Vol 32 (3) ◽  
pp. 675-687
Author(s):  
Hemant Jain ◽  
Balaji Padmanabhan ◽  
Paul A. Pavlou ◽  
T. S. Raghu
Keyword(s):  
Artificial Intelligence ◽  
Special Section ◽  
Human Intelligence ◽  
Work Organizations ◽  
Research Directions ◽  
Research Issues ◽  
Future Of Work ◽  
The Future ◽  
Recent Developments ◽  
Working Together

Recent developments in artificial intelligence (AI) have increased interest in combining AI with human intelligence to develop superior systems that augment human and artificial intelligence. In this paper, augmented intelligence informally means computers and humans working together, by design, to enhance one another, such that the intelligence of the resulting system improves. Intelligence augmentation (IA) can pool the joint intelligence of humans and computers to transform individual work, organizations, and society. Notably, applications of IA are beginning to emerge in several domains, such as cybersecurity, privacy, counterterrorism, and healthcare, among others. We provide a brief summary of papers in this special section that represent early attempts to address some of the rapidly emerging research issues. We also present a framework to guide research on IA and advocate for the important implications of IA for the future of work, organizations, and society. We conclude by outlining promising research directions based on this framework for the information systems and related disciplines.

scholarly journals RNA Interference and mRNA Silencing, 2004: How Far Will They Reach?

2004 ◽  
Vol 15 (2) ◽  
pp. 407-410 ◽  
Author(s):  
Thoru Pederson
Keyword(s):  
Gene Expression ◽  
Rna Interference ◽  
Gene Silencing ◽  
Rna Silencing ◽  
Regulation Of Gene Expression ◽  
Clinical Impact ◽  
Posttranscriptional Gene Silencing ◽  
Highly Effective ◽  
The Future ◽  
Recent Developments

The discoveries of RNA interference and RNA-mediated posttranscriptional gene silencing have opened an unanticipated new window on the regulation of gene expression as well as a facile and highly effective tool for knocking down gene expression in many organisms and cells. In addition, RNA interference and RNA silencing may conceivably be exploited for human therapeutics sometime in the future, possibly bringing greater clinical impact than have the so far disappointing antisense endeavors. This essay summarizes recent developments and offers some personalized perspectives, with emphasis on what we do not yet know.

scholarly journals Artificial Intelligence for Microscopy: What You Should Know

2019 ◽  
Author(s):  
Lucas von Chamier ◽  
Romain F. Laine ◽  
Ricardo Henriques
Keyword(s):  
Artificial Intelligence ◽  
Image Segmentation ◽  
Deep Learning ◽  
Information Content ◽  
Biomedical Research ◽  
Cell Biology ◽  
Future Directions ◽  
New Horizons ◽  
The Future ◽  
Recent Developments

Artificial Intelligence based on Deep Learning is opening new horizons in Biomedical research and promises to revolutionize the Microscopy field. Slowly, it now transitions from the hands of experts in Computer Sciences to researchers in Cell Biology. Here, we introduce recent developments in Deep Learning applied to Microscopy, in a manner accessible to non-experts. We overview its concepts, capabilities and limitations, presenting applications in image segmentation, classification and restoration. We discuss how Deep Learning shows an outstanding potential to push the limits of Microscopy, enhancing resolution, signal and information content in acquired data. Its pitfalls are carefully discussed, as well as the future directions expected in this field.

scholarly journals Artificial intelligence in the diagnosis of cardiovascular disease

2019 ◽  
Vol 65 (12) ◽  
pp. 1438-1441
Author(s):  
Rubens Moura Campos Zeron ◽  
Carlos Vicente Serrano Junior
Keyword(s):  
Artificial Intelligence ◽  
Potential Role ◽  
Clinical Care ◽  
Clinical Impact ◽  
Thought Processes ◽  
Cardiovascular Medicine ◽  
Human Thought ◽  
Quality Of Patient Care ◽  
Potential Clinical Impact

SUMMARY Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enabling cost-effectiveness, and reducing readmission and mortality rates. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI’s application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine.

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