OBJECTIVE: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal g...
Recently, explainability in machine and deep learning has become an important area in the field of research as well as interest, both due to the increasing use of artificial intelligence (AI) methods and understanding of the decisions made by models....
BACKGROUND: We investigated the potential of an imaging-aware GPT-4-based chatbot in providing diagnoses based on imaging descriptions of abdominal pathologies.
The scope of artificial intelligence (AI) in healthcare is promising, and AI has the potential to revolutionise the field of palliative care services also. Consumer satisfaction in palliative care is a critical aspect of providing high-quality end-of...
Microplastics pollution is killing human life, contaminating our oceans, and lasting for longer in the environment than it is used. Microplastics have contaminated the geochemistry and turned the water system into trash barrel. Its detection in water...
STUDY OBJECTIVE: This study aimed to prospectively validate the performance of an artificially augmented home sleep apnea testing device (WVU-device) and its patented technology.
Generative artificial intelligence (AI) has revolutionized medicine over the past several years. A generative adversarial network (GAN) is a deep learning framework that has become a powerful technique in medicine, particularly in ophthalmology for i...
PRCIS: In this meta-analysis of 6 studies and 5269 patients, deep learning algorithms applied to AS-OCT demonstrated excellent diagnostic performance for closed angle compared with gonioscopy, with a pooled sensitivity and specificity of 94% and 93.6...
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