AIMC Topic: Sensitivity and Specificity
Clear Filters Showing 2501 to 2510 of 2922 articles
Comprehensive analysis of clinical images contributions for melanoma classification using convolutional neural networks.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
May 1, 2024
BACKGROUND: Timely diagnosis plays a critical role in determining melanoma prognosis, prompting the development of deep learning models to aid clinicians. Questions persist regarding the efficacy of clinical images alone or in conjunction with dermos...
Diagnostic effectiveness of deep learning-based MRI in predicting multiple sclerosis: A meta-analysis.
Neurosciences (Riyadh, Saudi Arabia)
May 1, 2024
OBJECTIVES: The brain and spinal cord, constituting the central nervous system (CNS), could be impacted by an inflammatory disease known as multiple sclerosis (MS). The convolutional neural networks (CNN), a machine learning method, can detect lesion...
Artificial Intelligence for Breast Cancer Screening: Trade-offs between Sensitivity and Specificity.
Radiology. Artificial intelligence
May 1, 2024
Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time.
Radiology. Artificial intelligence
May 1, 2024
Purpose To develop an artificial intelligence (AI) model for the diagnosis of breast cancer on digital breast tomosynthesis (DBT) images and to investigate whether it could improve diagnostic accuracy and reduce radiologist reading time. Materials an...
Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.
Radiology. Artificial intelligence
May 1, 2024
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized m...
Diagnostic accuracy of artificial intelligence versus manual detection in marginal bone loss around fixed prosthesis. a systematic review.
JPMA. The Journal of the Pakistan Medical Association
Apr 1, 2024
OBJECTIVES: The aim of the review is to evaluate the existing precision of artificial intelligence (AI) in detecting Marginal Bone Loss (MBL) around prosthetic crowns using 2-Dimentional radiographs. It also summarises the recent advances and future ...
Arrhythmia classification based on multi-feature multi-path parallel deep convolutional neural networks and improved focal loss.
Mathematical biosciences and engineering : MBE
Mar 22, 2024
Early diagnosis of abnormal electrocardiogram (ECG) signals can provide useful information for the prevention and detection of arrhythmia diseases. Due to the similarities in Normal beat (N) and Supraventricular Premature Beat (S) categories and imba...
Deep learning for acute rib fracture detection in CT data: a systematic review and meta-analysis.
The British journal of radiology
Feb 28, 2024
OBJECTIVES: To review studies on deep learning (DL) models for classification, detection, and segmentation of rib fractures in CT data, to determine their risk of bias (ROB), and to analyse the performance of acute rib fracture detection models.
[Artificial intelligence in ultrasound diagnosis of thyroid nodules].
Khirurgiia
Jan 1, 2024
OBJECTIVE: To analyze the efficacy of the S-Detect AI system of the Samsung RS85 ultrasound scanner (South Korea) in stratifying thyroid nodules compared to data obtained by specialist of ultrasound diagnostics.
The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2024
BACKGROUND: Pulmonary nodule, one of the most common clinical phenomena, is an irregular circular lesion with a diameter of ⩽ 3 cm in the lungs, which can be classified as benign or malignant. Differentiating benign and malignant pulmonary nodules ha...
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