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Dento Maxillo Facial Radiology Mar 2021Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is...
Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is no exception to this trend, and the applications of artificial intelligence are particularly promising in the field of oral and maxillofacial (OMF) radiology. Recent researches on artificial intelligence in OMF radiology have mainly used convolutional neural networks, which can perform image classification, detection, segmentation, registration, generation, and refinement. Artificial intelligence systems in this field have been developed for the purposes of radiographic diagnosis, image analysis, forensic dentistry, and image quality improvement. Tremendous amounts of data are needed to achieve good results, and involvement of OMF radiologist is essential for making accurate and consistent data sets, which is a time-consuming task. In order to widely use artificial intelligence in actual clinical practice in the future, there are lots of problems to be solved, such as building up a huge amount of fine-labeled open data set, understanding of the judgment criteria of artificial intelligence, and DICOM hacking threats using artificial intelligence. If solutions to these problems are presented with the development of artificial intelligence, artificial intelligence will develop further in the future and is expected to play an important role in the development of automatic diagnosis systems, the establishment of treatment plans, and the fabrication of treatment tools. OMF radiologists, as professionals who thoroughly understand the characteristics of radiographic images, will play a very important role in the development of artificial intelligence applications in this field.
Topics: Artificial Intelligence; Humans; Neural Networks, Computer; Radiography; Radiologists; Radiology
PubMed: 33197209
DOI: 10.1259/dmfr.20200375 -
AJNR. American Journal of Neuroradiology Oct 2019
Topics: Cell- and Tissue-Based Therapy; Humans; Radiologists; Receptors, Chimeric Antigen
PubMed: 31537523
DOI: 10.3174/ajnr.A6231 -
Pediatric Radiology Jul 2021
Topics: COVID-19; Humans; Radiologists; Radiology; SARS-CoV-2
PubMed: 33730184
DOI: 10.1007/s00247-021-05036-5 -
AJNR. American Journal of Neuroradiology Feb 2018
Topics: Magnetic Resonance Imaging; Pacemaker, Artificial; Radiologists
PubMed: 29074630
DOI: 10.3174/ajnr.A5467 -
Pediatric Radiology Apr 2022The field of radiology has benefited greatly from the technological boom that has brought greater precision, efficiency and utilization amid an exponential growth in... (Review)
Review
The field of radiology has benefited greatly from the technological boom that has brought greater precision, efficiency and utilization amid an exponential growth in medical science. The downside is that the same technology that has allowed the field to grow is contributing to an erosion of interpersonal communication and connection with patients and referring physicians. Remote reading has displaced us from the communal reading room, where much interaction and teaching used to take place. The "invisible" radiologist must transcend these barriers in order to preserve and strengthen the role of radiology in medical care. With modest adaptation, radiologists can regain their identity as consultants, where they have the greatest chance to show their value and thwart the drive toward commoditization.
Topics: Communication; Humans; Radiography; Radiologists; Radiology; Referral and Consultation
PubMed: 34173851
DOI: 10.1007/s00247-021-05133-5 -
Radiologie (Heidelberg, Germany) Feb 2023Interdisciplinary case discussions, especially tumor conferences, represent a large part of the clinical radiologist's daily work. Radiology plays a key role in tumor... (Review)
Review
BACKGROUND
Interdisciplinary case discussions, especially tumor conferences, represent a large part of the clinical radiologist's daily work. Radiology plays a key role in tumor conferences, since imaging findings have a direct influence on therapy decisions.
METHODS AND OBJECTIVES
This article discusses the requirements for the radiologist in preparing and conducting tumor conferences. Furthermore, the general conditions and forms of implementation of tumor conferences will be highlighted. Information technology (IT) tools for process automation and systems for assessing the course of tumor diseases will be presented.
RESULTS
Detailed preparation of tumor conferences and clear communication of findings is essential. The radiological expertise in tumor conferences often leads to changes or adjustments of initially planned therapies. In addition to traditional face-to-face meetings, hybrid solutions have become established for tumor conferences in which the core team is on site and other participants (external referring physicians, internal participants outside the core team) are connected via video conference. Various systems have been established for assessing the course of tumor diseases. Due to its broad applicability, RECIST 1.1. is the most widely used. IT tools enable previously marked lesions to be displayed over time in a matrix view (lesion tracking). Artificial intelligence (AI) can also be used to automatically detect lesions and assess their volumes.
CONCLUSION
Preparing and conducting tumor conferences is time-consuming for radiologists. IT tools can automate and thus facilitate the processes. Hybrid solutions combining face-to-face meetings and video conferences make it easier for external referring physicians to present their patients in tumor conferences.
Topics: Humans; Artificial Intelligence; Radiology; Radiologists; Radiography; Communication
PubMed: 36629884
DOI: 10.1007/s00117-023-01114-x -
RoFo : Fortschritte Auf Dem Gebiete Der... May 2020
Topics: Curriculum; Germany; Humans; Radiography; Radiologists; Radiology
PubMed: 32316046
DOI: 10.1055/a-1091-4072 -
Diagnostic and Interventional Imaging Oct 2022
Topics: Artificial Intelligence; Humans; Radiologists; Radiology
PubMed: 35973913
DOI: 10.1016/j.diii.2022.08.001 -
European Journal of Radiology Oct 2022Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients... (Review)
Review
Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients can be challenging in the setting of busy radiology departments where there is a focus on efficient and accurate diagnosis. Traditionally, most results are provided directly to the referring clinician. However, the importance of direct communication between the radiologist and patient is increasingly relevant, particularly in the context of face-to-face settings such as rapid assessment and ultrasound clinics, and interventional radiology, as well as in written form through electronic patient portals. Artificial intelligence tools may improve efficiency, allowing more time for radiologists to communicate directly with patients. There is a need for dedicated training in communication skills for imaging professionals. This review considers the topic of patient communication in the setting of imaging departments and discusses the ways that communication skills may be improved through training and through harnessing emerging digital technologies that may enhance the quality of communication.
Topics: Artificial Intelligence; Communication; Humans; Radiography; Radiologists; Radiology
PubMed: 36038410
DOI: 10.1016/j.ejrad.2022.110464 -
Current Problems in Diagnostic Radiology 2022Radiologist wellness is important on an individual and group/institutional level and helps to promote a strong and healthy working environment, which can improve... (Review)
Review
Radiologist wellness is important on an individual and group/institutional level and helps to promote a strong and healthy working environment, which can improve radiologist retention and engagement. This paper will discuss case examples of radiologist wellness improvements in a single academic institution over a 3-year period using the DMAIC (Define, Measure, Analyze, Improve, and Control) model. Leveraging this framework led to the implementation of reading room assistants, reduction in work-related injuries by improvements in ergonomics, and the formation of a faculty mentorship program.
Topics: Humans; Radiologists
PubMed: 35365374
DOI: 10.1067/j.cpradiol.2022.02.006