A range of devices and technologies are available to mediate social connections between geographically distant people. Some of these methods exploit awareness information to enhance the connectedness of distant users. However, the effect of user trai...
BACKGROUND: Liver cirrhosis complicated by portal vein thrombosis (PVT) is a fatal complication with no specific manifestations but often misdiagnosed, it crucially increases the mortality worldwide. This study aimed to identify risk factors and esta...
OBJECTIVES: This study aimed to develop a multimodal radiopathomics model utilising preoperative ultrasound (US) and fine-needle aspiration cytology (FNAC) to predict large-number cervical lymph node metastasis (CLNM) in patients with clinically lymp...
AimThis study aimed to develop a web-based machine learning (ML) model to predict the lifetime likelihood of developing varicose veins using global disease prevalence data.MethodsWe utilized data from a systematic review, registered under PROSPERO (C...
PURPOSE: Many breast centers are unable to provide immediate results at the time of screening mammography which results in delayed patient care. Implementing artificial intelligence (AI) could identify patients who may have breast cancer and accelera...
OBJECTIVES: Ultrasound is a promising low-risk imaging modality that can provide objective airway measurements that may circumvent limitations of drug-induced sleep endoscopy (DISE). This study was devised to identify ultrasound-derived anatomical me...
AIM: Prospective outcome prediction plays a crucial role in guiding preoperative decision-making in patients with Chiari malformation type I (CM-Ⅰ) with syringomyelia. Here, we aimed to develop a predictive model for postoperative outcomes in patient...
AIM: To develop and validate a machine learning (ML) model based on positron emission tomography/computed tomography (PET/CT) multi-modality fusion radiomics to improve the prediction efficiency of mediastinal-hilar lymph node metastasis (LNM).
International journal of medical informatics
Jan 29, 2025
PURPOSE: To develop and validate a novel artificial intelligence model for predicting the initial empiric dose of vancomycin, with the aim of achieving an area under the concentration-time curve (AUC) of 400-600 mg∙h/L, using individual clinical data...
Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional connectivity matrix a...
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