Clinical care in ophthalmology is rapidly evolving as artificial intelligence (AI) algorithms are being developed. The medical community and national and federal regulatory bodies are recognizing the importance of adapting to AI. However, there is a gap in physicians' understanding of AI and its implications regarding its potential use in clinical care, and there are limited resources and established programs focused on AI and medical education in ophthalmology. Physicians are essential in the application of AI in a clinical context. An AI curriculum in ophthalmology can help provide physicians with a fund of knowledge and skills to integrate AI into their practice. In this paper, we provide general recommendations for an AI curriculum for medical students, residents, and fellows in ophthalmology.
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http://dx.doi.org/10.1167/tvst.10.7.14 | 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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