Latest AI and machine learning research in public health & policy for healthcare professionals.
This paper systematically reviews advancements in deep learning (DL) techniques for financial fraud detection, a critical issue in the financial sector. Using the Kitchenham systematic literature review approach, 57 studies published between 2019 and 2024 were analyzed. The review highlights the effectiveness of various deep learning models such as Convolutional Neural Networks, Long Short-Term ...
Breast cancer screening plays a pivotal role in early detection and subsequent effective management of the disease, impacting patient outcomes and survival rates. This study aims to assess breast cancer screening rates nationwide in the United States and investigate the impact of social determinants of health on these screening rates. Data on mammography screening at the census tract level for 2...
This study presents a narrative review of the use of digital health technologies (DHTs) and artificial intelligence to screen and mitigate risks and...
Antimicrobial-resistant (AMR) microbes are a growing challenge in healthcare, rendering modern medicines ineffective. AMR arises from antibiotic pro...
The rapid integration of the Internet of Things (IoT) and Internet of Medical (IoM) devices in the healthcare industry has markedly improved patient...
For rapidly spreading diseases where many cases show no symptoms, swift and effective contact tracing is essential. While exposure notification appl...
Healthcare decision-making requires not only accurate predictions but also insights into how factors influence patient outcomes. While traditional M...
This study addresses a critical gap in the healthcare system by developing a clinically meaningful, practical, and explainable disease surveillance ...
Video surveillance systems are crucial components for ensuring public safety and management in smart city. As a fundamental task in video surveillan...
Online gambling platforms have transformed the gambling landscape, offering unprecedented accessibility and personalized experiences. However, these...
Human Action Recognition (HAR) is a challenging domain in computer vision, involving recognizing complex patterns by analyzing the spatiotemporal dy...
Two modern trends in insurance are data-intensive underwriting and behavior-based insurance. Data-intensive underwriting means that insurers use and...
Deep learning based person re-identification (re-id) models have been widely employed in surveillance systems. Recent studies have demonstrated that...
Agile healthcare frameworks, derived from methodologies in IT and manufacturing, offer transformative potential for low-income regions. This study e...
Understanding the prevalence, disparities, and symptom variations of Post COVID-19 Condition (PCC) for vulnerable populations is crucial to improvin...
While tobacco advertising innovates at unprecedented speed, traditional surveillance methods remain frozen in time, especially in the context of soc...
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with lung metastases being the most common site of distant spread and...
Longitudinal MRI analysis is crucial for predicting disease outcomes, particularly in chronic conditions like hepatocellular carcinoma (HCC), where ...
With the rapid development of digital services, a large volume of personally identifiable information (PII) is stored online and is subject to cyber...
OBJECTIVE: To conduct a systematic review on Artificial Intelligence-Mediated Communication (AIMC) behavioral interventions in cancer prevention/contr...