Assessing Bone Age: A Paradigm for the Next Generation of Artificial Intelligence in Radiology

Radiology ◽  
2021 ◽  
pp. 211339
Author(s):  
David A. Rubin
2020 ◽  
Vol 24 (01) ◽  
pp. 38-49 ◽  
Author(s):  
Natalia Gorelik ◽  
Jaron Chong ◽  
Dana J. Lin

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.


2021 ◽  
Vol 11 (1) ◽  
pp. 74-83
Author(s):  
John Kang ◽  
Reid F. Thompson ◽  
Sanjay Aneja ◽  
Constance Lehman ◽  
Andrew Trister ◽  
...  

2020 ◽  
pp. 1-5
Author(s):  
Bahman Zohuri ◽  
◽  
Farhang Mossavar Rahmani ◽  

Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame.


2011 ◽  
pp. 89-100
Author(s):  
Ali Jafari

Today’s portals bring together existing technologies in useful, innovative ways, but they don’t scratch the surface of what is possible. The constant build-up of information and resources on the World Wide Web demands a smarter more advanced portal technology that offers dynamic, personalized, customized, and intelligent services. This chapter discusses next-generation portals and the requirement that they come to know their users and understand their individual interests and preferences. It describes a new generation of portals that have a level of autonomy, making informed, logical decisions and performing useful tasks on behalf of their members. The chapter highlights the role of artificial intelligence in framing the next generation of portal technology and in developing their capabilities for learning about their users.


Author(s):  
Rinat Galiautdinov

The chapter describes the new approach in artificial intelligence based on simulated biological neurons and creation of the neural circuits for the sphere of IoT which represent the next generation of artificial intelligence and IoT. Unlike existing technical devices for implementing a neuron based on classical nodes oriented to binary processing, the proposed path is based on simulation of biological neurons, creation of biologically close neural circuits where every device will implement the function of either a sensor or a “muscle” in the frame of the home-based live AI and IoT. The research demonstrates the developed nervous circuit constructor and its usage in building of the AI (neural circuit) for IoT.


2020 ◽  
pp. 1-8
Author(s):  
Xiao Liu ◽  
Mingzhe Chen ◽  
Yuanwei Liu ◽  
Yue Chen ◽  
Shuguang Cui ◽  
...  

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