OBJECTIVE: The accuracy of deep learning models for many disease prediction problems is affected by time-varying covariates, rare incidence, covariate imbalance and delayed diagnosis when using structured electronic health records data. The situation...
Although the use of immune checkpoint inhibitors (ICIs)-targeted agents for unresectable hepatocellular carcinoma (HCC) is promising, individual response variability exists. Therefore, we developed an artificial intelligence (AI)-based model to predi...
Acta radiologica (Stockholm, Sweden : 1987)
Mar 15, 2024
BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate and advanced hepatocellular carcinoma (HCC), with the potential to enhance patient survival. Preoperative prediction of postoperative response to TAC...
. Precise hepatocellular carcinoma (HCC) detection is crucial for clinical management. While studies focus on computed tomography-based automatic algorithms, there is a rareness of research on automatic detection based on dynamic contrast enhanced (D...
Journal of imaging informatics in medicine
Mar 4, 2024
Due to the increasing interest in the use of artificial intelligence (AI) algorithms in hepatocellular carcinoma detection, we performed a systematic review and meta-analysis to pool the data on diagnostic performance metrics of AI and to compare the...
Liver international : official journal of the International Association for the Study of the Liver
Mar 4, 2024
BACKGROUND AND AIMS: Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI ...
PURPOSE: To investigate the value of a multimodal deep learning (MDL) model based on computed tomography (CT) and magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).
PURPOSE: Segmentation of hepatocellular carcinoma (HCC) is crucial; however, manual segmentation is subjective and time-consuming. Accurate and automatic lesion contouring for HCC is desirable in clinical practice. In response to this need, our study...
Journal of imaging informatics in medicine
Feb 23, 2024
The goal of this study was to evaluate the performance of a convolutional neural network (CNN) with preoperative MRI and clinical factors in predicting the treatment response of unresectable hepatocellular carcinoma (HCC) patients receiving hepatic a...
BACKGROUND: Artificial intelligence (AI)-assisted clinical trial screening is a promising prospect, although previous matching systems were developed in English, and relevant studies have only been conducted in Western countries. Therefore, we evalua...