Latest AI and machine learning research in domestic violence for healthcare professionals.
The integration of large language models (LLM) into the care of trauma surgery patients offers an exciting opportunity with immense potential to enhance the efficiency and quality of care. The LLM can serve as supportive tools for diagnosis, decision making and patient communication by efficiently providing medical knowledge and generating personalized treatment recommendations; however, there are...
The prevention and control of emerging and reemerging infectious diseases are crucial for national biosecurity, and surveillance and reporting of pneumonia of unknown etiology are main ways for the early detection of these diseases and mitigation of their severity. This paper summaries the surveillance methods for pneumonia of unknown etiology and emerging and reemerging infectious diseases global...
BACKGROUND: Breast cancer screening is considered an effective early detection strategy. Artificial intelligence (AI) may both offer benefits and crea...
Accurate diagnosis of orthopedic injuries, especially pelvic and hip fractures, is vital in trauma management. While pelvic radiographs (PXRs) are wid...
Butyrylcholinesterase (BChE), plays a critical role in alleviating the symptoms of Alzheimer's disease (AD) by regulating acetylcholine levels, emergi...
BACKGROUND: Artificial intelligence (AI) is a promising tool used in oncology that may be able to facilitate diagnosis, treatment planning, and patien...
Globally, mental disorders are a significant burden, particularly in low- and middle-income countries, with high prevalence in Rwanda, especially amon...
Purpose: With advancements in Large Language Models (LLMs) for healthcare, the need arises for competitive open-source models to protect the public ...
AIMS: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural opt...
Harmonization of T1-weighted MR images across different scanners is crucial for ensuring consistency in neuroimaging studies. This study introduces ...
Emerging contaminants (ECs) can exert irreversible health impacts on humans, even at trace concentrations. Currently, nontargeted screening of ECs has...
Purpose To evaluate cancer detection and marker placement accuracy of two artificial intelligence (AI) models developed for interpretation of screenin...
Purpose To test a commercial artificial intelligence (AI) system for breast cancer detection at the BC Cancer Breast Screening Program. Materials and ...
Background Chest pain is a leading cause of outpatient and emergency department visits; advancements in artificial intelligence (AI) could improve cor...
Diabetic retinopathy (DR) is a frequent complication of diabetes, affecting millions worldwide. Screening for this disease based on fundus images has ...
Purpose To assess patient perceptions of artificial intelligence (AI) use in the interpretation of screening mammograms. Materials and Methods In a pr...
In recent years, the research and development (R&D) of rice and wheat functional foods has attracted a widespread attention from food researchers, dri...
BACKGROUND: Artificial intelligence (AI) could improve accuracy and efficiency of breast cancer screening. However, many women distrust AI in health c...
BACKGROUND: Sjögren's Disease (SjD) is histopathologically characterized by focal sialadenitis in minor labial salivary gland biopsies (mLSGB), which ...
Objectives: While Large Language Models (LLMs) have been widely used to assist clinicians and support patients, no existing work has explored dialog...