OBJECTIVE: To develop and validate a deep neural network (DNN) model for diagnosing Parkinson's Disease (PD) using handwritten spiral and wave images, and to compare its performance with various machine learning (ML) and deep learning (DL) models.
OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).
OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patients with acute gastrointestinal bleeding (AGIB) in the intensive care unit (ICU) and compared their prognostic performance with that of Acute Physiolo...
The medical metaverse is a combination of medicine, computer science, information technology and other cutting-edge technologies. It redefines the method of information interaction about doctor-patient communication, medical education and research th...
OBJECTIVE: Behavioral interventions have been shown to ameliorate the electroencephalogram (EEG) dynamics underlying the behavioral symptoms of autism spectrum disorder (ASD), while studies have also demonstrated that mirror neuron mu rhythm-based EE...
Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with the rapid development of machine learning (ML) and deep learning (DL), significant progress has been m...
OBJECTIVE: To evaluate the accuracy and parsing ability of GPT 4.0 for Japanese medical practitioner qualification examinations in a multidimensional way to investigate its response accuracy and comprehensiveness to medical knowledge.
BACKGROUND AND OBJECTIVE: The effectiveness of radiofrequency ablation (RFA) in improving long-term survival outcomes for patients with a solitary hepatocellular carcinoma (HCC) measuring 5 cm or less remains uncertain. This study was designed to elu...
OBJECTIVE: This study aims to construct and validate a predictable deep learning model associated with clinical data and multi-sequence magnetic resonance imaging (MRI) for short-term postoperative facial nerve function in patients with acoustic neur...
OBJECTIVE: The annual influenza epidemic is a heavy burden on the health care system, and has increasingly become a major public health problem in some areas, such as Hong Kong (China). Therefore, based on a variety of machine learning methods, and c...