Latest AI and machine learning research in domestic violence for healthcare professionals.
Background: Recruitment for cohorts involving complex liver diseases, such as hepatocellular carcinoma and liver cirrhosis, often requires interpreting semantically complex criteria. Traditional manual screening methods are time-consuming and prone to errors. While AI-powered pre-screening offers potential solutions, challenges remain regarding accuracy, efficiency, and data privacy. Methods: We...
Generative artificial intelligence holds significant potential for abuse, and generative image detection has become a key focus of research. However, existing methods primarily focused on detecting a specific generative model and emphasizing the localization of synthetic regions, while neglecting the interference caused by image size and style on model learning. Our goal is to reach a fundamenta...
Detecting phishing, spam, fake accounts, data scraping, and other malicious activity in online social networks (OSNs) is a problem that has been stu...
Educational technologies are revolutionizing how educational institutions operate. Consequently, it makes them a lucrative target for breach and abu...
Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesio...
Mental health remains a challenging problem all over the world, with issues like depression, anxiety becoming increasingly common. Large Language Mo...
Image watermarks have been considered a promising technique to help detect AI-generated content, which can be used to protect copyright or prevent f...
Cervical cancer is a leading malignancy in female reproductive system. While AI-assisted cytology offers a cost-effective and non-invasive screening...
When an individual reports a negative interaction with some system, how can their personal experience be contextualized within broader patterns of s...
Screening is a time-consuming and labour-intensive yet required task for medical systematic reviews, as tens of thousands of studies often need to b...
Deep Learning approaches in dermatological image classification have shown promising results, yet the field faces significant methodological challen...
OBJECTIVES: To evaluate the interobserver agreement and diagnostic accuracy of ovarian-adnexal reporting and data system magnetic resonance imaging (O...
Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no o...
Purpose To evaluate the change in digital breast tomosynthesis artificial intelligence (DBT-AI) case scores over sequential screenings. Materials and ...
Background Combined mammography and MRI screening is not universally accessible for women with intermediate breast cancer risk due to limited MRI reso...
Breast cancer screening plays a pivotal role in early detection and subsequent effective management of the disease, impacting patient outcomes and s...
Bluetooth Low Energy (BLE) location trackers, or "tags", are popular consumer devices for monitoring personal items. These tags rely on their respec...
Importance: Emergency department (ED) returns for mental health conditions pose a major healthcare burden, with 24-27% of patients returning within ...
Understanding the prevalence, disparities, and symptom variations of Post COVID-19 Condition (PCC) for vulnerable populations is crucial to improvin...
Age prediction using brain imaging, such as MRIs, has achieved promising results, with several studies identifying the model's residual as a potenti...