Artificial Intelligence (AI) consists of setting different technics together aimed at allowing machines to simulate human cognitive fonctions, mimic human brain functions, sometime its logic, when it comes to answer to an interrogation, to take decisions or to anticipate events. This new fonction, after being used in numerous daily life domains (geo-guides, personal assistants, administratif procedures) comes now in the medical area. The press exaggerations on those systems doesn't have any wise and thoughtful judgment. This article will talk about the question of the real uses and expertise capacities which the AI should be able to provide in our area. Through the history of cognitive science and ideas, the recension of important works on the AI developments, we want to put in perspective the promises and opportunities provided to modify or complete the expertise in orthodontics. The willingness to extend cognitive and action abilities is older than what the comma historiography of the AI let us think. The recent development of computer systems, algorithmic science and databases allowed the development of a branch of the artificial intelligent giving, in some cases, seemingly undeniable results which should not be extrapolated because of the weakness of our databases, the current economic model and their real use.
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http://dx.doi.org/10.1684/orthodfr.2020.10 | DOI Listing |
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFEur J Radiol
January 2025
Department of Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany; Institute of Medical Physics, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany. Electronic address:
Objectives: Contrast agents are frequently administered in computed tomography (CT) scans used for opportunistic screening of osteoporosis. The objective of this study is to compare the impact of contrast-related bone mineral density (BMD) increase between phantom-based and internal CT calibration techniques.
Materials And Methods: Phantom-based and internal CT calibration techniques were used to determine trabecular BMD in 93 existing clinical CT scans of the lumbar spine of 34 subjects, scanned before and after administration of contrast agents.
J Neurosurg
January 2025
1Department of Neurosurgery, St. Olav's University Hospital, Trondheim, Norway.
Objective: The extent of resection (EOR) and postoperative residual tumor (RT) volume are prognostic factors in glioblastoma. Calculations of EOR and RT rely on accurate tumor segmentations. Raidionics is an open-access software that enables automatic segmentation of preoperative and early postoperative glioblastoma using pretrained deep learning models.
View Article and Find Full Text PDFJCO Precis Oncol
January 2025
Translational Research Support Office, National Cancer Center Hospital East, Chiba, Japan.
Purpose: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mCRC). Identifying optimal biomarkers for treatment decisions remains challenging. This study explores the potential of artificial intelligence (AI) in predicting treatment responses to trastuzumab plus pertuzumab (TP) in patients with -amplified mCRC from the phase II TRIUMPH trial.
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