Latest AI and machine learning research in surveillance for healthcare professionals.
Transit Origin-Destination (OD) data are essential for transit planning, particularly in route optimization and demand-responsive paratransit systems. Traditional methods, such as manual surveys, are costly and inefficient, while Bluetooth and WiFi-based approaches require passengers to carry specific devices, limiting data coverage. On the other hand, most transit vehicles are equipped with onb...
Bias in data collection, arising from both under-reporting and over-reporting, poses significant challenges in critical applications such as healthcare and public safety. In this work, we introduce Graph-based Over- and Under-reporting Debiasing (GROUD), a novel graph-based optimization framework that debiases reported data by jointly estimating the true incident counts and the associated report...
Radiologists routinely detect and size lesions in CT to stage cancer and assess tumor burden. To potentially aid their efforts, multiple lesion dete...
Composite lymphoma (CL) is rare. We conducted an analysis of 53 329 cases of diffuse large B-cell lymphoma (DLBCL), 17,916 cases of Hodgkin lymphoma (...
The challenge of detecting violent incidents in urban surveillance systems is compounded by the voluminous and diverse nature of video data. This pa...
Remote tracking systems play a critical role in applications such as IoT, monitoring, surveillance and healthcare. In such systems, maintaining both...
Cardiovascular diseases remain the leading cause of global morbidity and mortality. Validated risk scores are the basis of guideline-recommended care,...
Background Limited data are available regarding the accuracy of artificial intelligence (AI) algorithms trained on bilateral mammograms for second bre...
This document defines the key considerations for developing and reporting an artificial intelligence (AI) interpretation model for the detection of cl...
Hospital-acquired infections (HAIs) significantly burden global healthcare systems, exacerbated by antibiotic-resistant bacteria. Traditional infectio...
Background Standardized bone tumor reporting is crucial for consistent, risk-aligned patient management. Current systems are based on expert consensus...
Background Ovarian-Adnexal Reporting and Data System (O-RADS) for MRI helps assign malignancy risk, but radiologist adoption is inconsistent. Automati...
We introduce a novel task of generating realistic and diverse 3D hand trajectories given a single image of an object, which could be involved in a h...
This paper introduces a novel framework that combines traditional centrality measures with eigenvalue spectra and diffusion processes for a more com...
In this paper, we present a simple method to integrate risk-contact data, obtained via digital contact monitoring (DCM) apps, in conventional compar...
Small object detection (SOD) is a critical yet challenging task in computer vision, with applications like spanning surveillance, autonomous systems...
Automated one-to-many (1:N) face recognition is a powerful investigative tool commonly used by law enforcement agencies. In this context, potential ...
The aim of this study was to devise a machine learning algorithm with superior performance in predicting bone metastasis (BM) in small cell lung cance...
This paper introduces AIJIM, the Artificial Intelligence Journalism Integration Model -- a novel framework for integrating real-time AI into environ...
Proceedings of the 3rd Italian Conference on Big Data and Data Science (ITADATA2024), held in Pisa, Italy, September 17-19, 2024. The Italian Conf...