Results 271 to 280 of about 379,277 (342)

Appropriateness of Recommendations Provided by ChatGPT to Interventional Radiologists

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes, 2023
Purpose: The purpose of this study was to analyze the answers provided by ChatGPT to various questions in the field of interventional radiology (IR) and compare their correctness to a consensus of three interventional radiologists. Materials and Methods.
M. Barat, P. Soyer, A. Dohan
semanticscholar   +1 more source

The Disruptive Radiologist

Journal of the American College of Radiology, 2015
Radiologists interact with many individuals during daily practice, including patients, technologists, and other physicians. Some interactions may potentially negatively affect patient care and are termed "disruptive" behaviors. These actions are not uncommon and may begin during training, long before a radiologist enters clinical practice.
Sidney, Ulreich, Robert D, Harris, Gordon, Sze, Andrew K, Moriarity, Edward, Bluth   +4 more
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The disruptive radiologist

Clinical Imaging, 2022
Hospital and regulatory organizations recognize the downstream impact of interpersonal relationships on patient safety. There are many contributors to interpersonal dynamics, one of which includes disruptive physicians. This can stem from overt or passive behaviors and has been categorized in the literature by terms that include disruptive physicians ...
Karen E, Gerlach, Kanchan A, Phalak, Jay R, Parikh   +2 more
openaire   +2 more sources

The Impaired Radiologist

Journal of the American College of Radiology, 2015
Radiologists are faced with ever-increasing challenges in the needs of the practice, in both private and academic settings. Targeted information about protecting and maintaining the physical, mental, and emotional health of the radiologist is highly limited.
Claire E, Bender, Marta E, Heilbrun, Hang B, Truong, Edward I, Bluth   +3 more
openaire   +2 more sources

Deep Learning: An Update for Radiologists.

Radiographics, 2021
Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the image ...
P. Cheng, E. Montagnon, R. Yamashita, I. Pan, A. Cadrin-Chênevert, Francisco Perdigón Romero, G. Chartrand, S. Kadoury, A. Tang   +8 more
semanticscholar   +1 more source

Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists.

Radiology, 2022
Background The World Health Organization (WHO) recommends chest radiography to facilitate tuberculosis (TB) screening. However, chest radiograph interpretation expertise remains limited in many regions.
Sahar Kazemzadeh, Jin Yu, Shahar Jamshy, Rory Pilgrim, Zaid Nabulsi, Christina Chen, Neeral Beladia, Charles Lau, S. McKinney, Thad Hughes, A. Kiraly, Sreenivasa Raju Kalidindi, M. Muyoyeta, Jameson Malemela, Ting Shih, G. Corrado, L. Peng, Katherine Chou, Po-Hsuan Cameron Chen, Yun Liu, K. Eswaran, Daniel Tse, S. Shetty, Shruthi Prabhakara   +23 more
semanticscholar   +1 more source

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

The Lancet Oncology
Summary Background Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists.
A. Saha, J. Bosma, Jasper J. Twilt, Bram van Ginneken, A. Bjartell, A. Padhani, D. Bonekamp, G. Villeirs, Georg Salomon, G. Giannarini, Jayashree Kalpathy-Cramer, J. Barentsz, Klaus Maier-Hein, M. Rusu, Olivier Rouvière, R. V. D. van den Bergh, V. Panebianco, V. Kasivisvanathan, N. Obuchowski, Derya Yakar, M. Elschot, J. Veltman, J. Fütterer, M. de Rooij, Henkjan Huisman   +24 more
semanticscholar   +1 more source

The Radiologist as a Consultant

JAMA: The Journal of the American Medical Association, 1982
To the Editor.— The following is in response to the view of Marc J. Homer, MD (1981;246:2581), that the radiologist should be considered as a consultant and to his comments in answer to Warren Bosley, MD (1982; 247:2233). It is commonly accepted practice in most hospitals that a consultant consults when he is invited to do so by the attending ...
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Comparing Diagnostic Accuracy of Radiologists versus GPT-4V and Gemini Pro Vision Using Image Inputs from Diagnosis Please Cases.

Radiology
Background The diagnostic abilities of multimodal large language models (LLMs) using direct image inputs and the impact of the temperature parameter of LLMs remain unexplored.
Pae Sun Suh, Woo Hyun Shim, C. H. Suh, H. Heo, Chae Ri Park, H. Eom, K. Park, J. Choe, Pyeong Hwa Kim, Hyo Jung Park, Yura Ahn, H. Park, Yoonseok Choi, Chang-Yun Woo, H. Park   +14 more
semanticscholar   +1 more source

Role of the Radiologist

JAMA: The Journal of the American Medical Association, 1982
To the Editor.— I was pleased to see that Marc J. Homer, MD, in the COMMENTARY "The Role of the Radiologist" (1981;246:2581), suggests that "the x-ray requisition should be viewed as a request for a consultation rather than an order." I have long questioned the practice of a radiologist interpreting all x-ray films that are taken in the hospital.
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