scholarly journals Artificial intelligence and colonoscopy: Current status and future perspectives

2019 ◽  
Vol 31 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Shin‐ei Kudo ◽  
Yuichi Mori ◽  
Masashi Misawa ◽  
Kenichi Takeda ◽  
Toyoki Kudo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Current Status ◽  
Future Perspectives

scholarly journals Use of artificial intelligence in imaging in rheumatology – current status and future perspectives

RMD Open ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. e001063 ◽  
Author(s):  
Berend Stoel
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Basic Research ◽  
Current Status ◽  
Future Perspectives ◽  
Clinical Imaging ◽  
The World ◽  
Human Interpretation ◽  
The Impact ◽  
Insight Into

After decades of basic research with many setbacks, artificial intelligence (AI) has recently obtained significant breakthroughs, enabling computer programs to outperform human interpretation of medical images in very specific areas. After this shock wave that probably exceeds the impact of the first AI victory of defeating the world chess champion in 1997, some reflection may be appropriate on the consequences for clinical imaging in rheumatology. In this narrative review, a short explanation is given about the various AI techniques, including ‘deep learning’, and how these have been applied to rheumatological imaging, focussing on rheumatoid arthritis and systemic sclerosis as examples. By discussing the principle limitations of AI and deep learning, this review aims to give insight into possible future perspectives of AI applications in rheumatology.

scholarly journals Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives

2020 ◽  
Vol 41 (3) ◽  
pp. 373-379 ◽  
Author(s):  
Z. Shi ◽  
B. Hu ◽  
U.J. Schoepf ◽  
R.H. Savage ◽  
D.M. Dargis ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intracranial Aneurysms ◽  
Current Status ◽  
Future Perspectives

scholarly journals Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Anke Meyer-Bäse ◽  
Lia Morra ◽  
Uwe Meyer-Bäse ◽  
Katja Pinker
Keyword(s):  
Artificial Intelligence ◽  
Magnetic Resonance ◽  
Breast Imaging ◽  
Clinical Decision Making ◽  
Therapy Monitoring ◽  
Breast Mri ◽  
Clinical Decision ◽  
Current Status ◽  
Imaging Biomarkers ◽  
Future Perspectives

Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications including screening, staging, and therapy monitoring. The rapid development and subsequent implementation of AI into clinical breast MRI has the potential to affect clinical decision-making, guide treatment selection, and improve patient outcomes. The goal of this review is to provide a comprehensive picture of the current status and future perspectives of AI in breast MRI. We will review DL applications and compare them to standard data-driven techniques. We will emphasize the important aspect of developing quantitative imaging biomarkers for precision medicine and the potential of breast MRI and DL in this context. Finally, we will discuss future challenges of DL applications for breast MRI and an AI-augmented clinical decision strategy.

Role of Pharmacogenomics in Antiepileptic Drug Therapy: Current Status and Future Perspectives

2018 ◽  
Vol 23 (37) ◽  
pp. 5760-5765 ◽  
Author(s):  
Antonio Gambardella ◽  
Angelo Labate ◽  
Laura Mumoli ◽  
Iscia Lopes-Cendes ◽  
Fernando Cendes
Keyword(s):  
Drug Therapy ◽  
Antiepileptic Drug ◽  
Current Status ◽  
Future Perspectives ◽  
Antiepileptic Drug Therapy
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