Latest AI and machine learning research in surveillance for healthcare professionals.
Arachnoid cysts are cerebrospinal fluid (CSF)-filled sacs that develop within the arachnoid membrane...
Background Chest pain is a leading cause of outpatient and emergency department visits; advancements...
BACKGROUND: Sjögren's Disease (SjD) is histopathologically characterized by focal sialadenitis in mi...
Medical image reporting (MIR) aims to generate structured clinical descriptions from radiological ...
Nowadays, social media is the main tool in our new lives. The outbreak news and all related obtain...
We present a Bayesian dynamic borrowing (BDB) approach to enhance the quantitative identification ...
Transit Origin-Destination (OD) data are essential for transit planning, particularly in route opt...
Bias in data collection, arising from both under-reporting and over-reporting, poses significant c...
Radiologists routinely detect and size lesions in CT to stage cancer and assess tumor burden. To p...
Composite lymphoma (CL) is rare. We conducted an analysis of 53 329 cases of diffuse large B-cell ly...
The challenge of detecting violent incidents in urban surveillance systems is compounded by the vo...
Remote tracking systems play a critical role in applications such as IoT, monitoring, surveillance...
Cardiovascular diseases remain the leading cause of global morbidity and mortality. Validated risk s...
Background Limited data are available regarding the accuracy of artificial intelligence (AI) algorit...
This document defines the key considerations for developing and reporting an artificial intelligence...
Hospital-acquired infections (HAIs) significantly burden global healthcare systems, exacerbated by a...
Background Standardized bone tumor reporting is crucial for consistent, risk-aligned patient managem...
Background Ovarian-Adnexal Reporting and Data System (O-RADS) for MRI helps assign malignancy risk, ...
We introduce a novel task of generating realistic and diverse 3D hand trajectories given a single ...
This paper introduces a novel framework that combines traditional centrality measures with eigenva...
In this paper, we present a simple method to integrate risk-contact data, obtained via digital con...