BACKGROUND: Systematic review is an indispensable tool for optimal evidence collection and evaluation in evidence-based medicine. However, the explosive increase of the original literatures makes it difficult to accomplish critical appraisal and regu...
The purpose of the paper was the assessment of the success of an artificial intelligence (AI) algorithm formed on a deep-convolutional neural network (D-CNN) model for the segmentation of apical lesions on dental panoramic radiographs. A total of 470...
Psoriasis is a chronic inflammatory skin disorder mediated by the immune response that affects a large number of people. According to latest worldwide statistics, 125 million individuals are suffering from psoriasis. Deep learning techniques have dem...
Error-driven learning algorithms, which iteratively adjust expectations based on prediction error, are the basis for a vast array of computational models in the brain and cognitive sciences that often differ widely in their precise form and applicati...
INTRODUCTION: The objectives of this study were to identify consensus priority research questions according to members of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES), and to explore differences in priorities according to ...
Artificial intelligence (AI), including deep learning methods that leverage neural network-based algorithms, hold significant promise for dermatopathology and other areas of diagnostic pathology in research and clinical practice. There has been signi...
Computer methods and programs in biomedicine
Jan 14, 2022
BACKGROUND AND OBJECTIVE: Medical image classification is often challenging for two reasons: a lack of labelled examples due to expensive and time-consuming annotation protocols, and imbalanced class labels due to the relative scarcity of disease-pos...
Cell detection and tracking applied to in vivo fluorescence microscopy has become an essential tool in biomedicine to characterize 4D (3D space plus time) biological processes at the cellular level. Traditional approaches to cell motion analysis by m...
In this paper, we propose a novel deep learning method for joint classification and segmentation of breast masses based on radio-frequency (RF) ultrasound (US) data. In comparison to commonly used classification and segmentation techniques, utilizing...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.