Medical image synthesis represents a critical area of research in clinical decision-making, aiming to overcome the challenges associated with acquiring multiple image modalities for an accurate clinical workflow. This approach proves beneficial in es...
Echocardiography plays a crucial role in diagnosis of cardiovascular diseases. Artificial intelligence has emerged as a high-precision tool to automate echocardiographic analysis. This review discusses AI algorithms that have been utilized at various...
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Dec 1, 2023
Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB),...
Cumulus expansion is an important indicator of oocyte maturation and has been suggested to be indicative of greater oocyte developmental capacity. Although multiple methods have been described to assess cumulus expansion, none of them is considered a...
The distinction between Xanthogranulomatous Cholecystitis (XGC) and Gallbladder Carcinoma (GBC) is challenging due to their similar imaging features. This study aimed to differentiate between XGC and GBC using a deep learning nomogram model built fro...
BACKGROUND: A major hurdle for the real time deployment of the AI models is ensuring trustworthiness of these models for the unseen population. More often than not, these complex models are black boxes in which promising results are generated. Howeve...
Retinitis pigmentosa (RP) is often undetected in its early stages. Artificial intelligence (AI) has emerged as a promising tool in medical diagnostics. Therefore, we conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy ...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Dec 1, 2023
PURPOSE: This study aimed to develop a deep learning (DL) method for noise quantification for clinical chest computed tomography (CT) images without the need for repeated scanning or homogeneous tissue regions.
This study examined preschoolers' trust toward accurate and inaccurate robot informants versus human informants. Singaporean children aged 3-5 years (N = 120, 57 girls, mostly Asian; data collected from 2017 to 2018) viewed either a robot or a human ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.