AIMC Topic: Radiologists
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Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities.
Nature communications
Sep 2, 2024
Multi-sequence magnetic resonance imaging is crucial in accurately identifying knee abnormalities but requires substantial expertise from radiologists to interpret. Here, we introduce a deep learning model incorporating co-plane attention across imag...
Comparative analysis of GPT-4-based ChatGPT's diagnostic performance with radiologists using real-world radiology reports of brain tumors.
European radiology
Aug 28, 2024
OBJECTIVES: Large language models like GPT-4 have demonstrated potential for diagnosis in radiology. Previous studies investigating this potential primarily utilized quizzes from academic journals. This study aimed to assess the diagnostic capabiliti...
Radiology staff perspectives are a key determinant for successful AI adoption in clinical practice.
European journal of radiology
Aug 22, 2024
Artificial intelligence in musculoskeletal applications: a primer for radiologists.
Diagnostic and interventional radiology (Ankara, Turkey)
Aug 19, 2024
As an umbrella term, artificial intelligence (AI) covers machine learning and deep learning. This review aimed to elaborate on these terms to act as a primer for radiologists to learn more about the algorithms commonly used in musculoskeletal radiolo...
Simulated arbitration of discordance between radiologists and artificial intelligence interpretation of breast cancer screening mammograms.
Journal of medical screening
Aug 11, 2024
Artificial intelligence (AI) algorithms have been retrospectively evaluated as replacement for one radiologist in screening mammography double-reading; however, methods for resolving discordance between radiologists and AI in the absence of 'real-wor...
Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jul 25, 2024
OBJECTIVES: Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the breast tissue. In a few cases, erroneous diagnosis of breast cancer by specialists and unnecessary biopsies can lead to various negative consequences. In ...
The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice.
BMC medicine
Jul 12, 2024
BACKGROUND: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histop...
Characterizing Sentinel Lymph Node Status in Breast Cancer Patients Using a Deep-Learning Model Compared With Radiologists' Analysis of Grayscale Ultrasound and Lymphosonography.
Ultrasound quarterly
Jul 3, 2024
The objective of the study was to use a deep learning model to differentiate between benign and malignant sentinel lymph nodes (SLNs) in patients with breast cancer compared to radiologists' assessments.Seventy-nine women with breast cancer were enro...
Radiologists' perceptions on AI integration: An in-depth survey study.
European journal of radiology
Jun 27, 2024
PURPOSE: To assess the perceptions and attitudes of radiologists toward the adoption of artificial intelligence (AI) in clinical practice.
Editorial Comment: The Radiologist's Role in Artificial Intelligence for Pediatric Oncologic Imaging.
AJR. American journal of roentgenology
Jun 12, 2024
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