BACKGROUND: To develop machine learning (ML) models predicting unplanned readmission and reoperation among patients undergoing free flap reconstruction for head and neck (HN) surgery.
Journal of imaging informatics in medicine
Feb 12, 2024
Convolutional Neural Networks have been widely applied in medical image segmentation. However, the existence of local inductive bias in convolutional operations restricts the modeling of long-term dependencies. The introduction of Transformer enables...
Journal of neurointerventional surgery
Feb 12, 2024
BACKGROUND: Artificial intelligence (AI) has become a promising tool in medicine. ChatGPT, a large language model AI Chatbot, shows promise in supporting clinical practice. We assess the potential of ChatGPT as a clinical reasoning tool for mechanica...
INTRODUCTION: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to those of certified dentists. This methodological systematic review aimed to evaluate the different ...
The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evalu...
BACKGROUND: Pretraining labeled datasets, like ImageNet, have become a technical standard in advanced medical image analysis. However, the emergence of self-supervised learning (SSL), which leverages unlabeled data to learn robust features, presents ...
Transcription profiling is a key process that can reveal those biological mechanisms driving the response to various exposure conditions or gene perturbations. In this work, we investigate the prediction of differentially expressed genes (DEGs) when ...
BACKGROUND: An adverse drug event (ADE) is any unfavorable effect that occurs due to the use of a drug. Extracting ADEs from unstructured clinical notes is essential to biomedical text extraction research because it helps with pharmacovigilance and p...
Journal of chemical information and modeling
Feb 6, 2024
Machine learning (ML) methods can train a model to predict material properties by exploiting patterns in materials databases that arise from structure-property relationships. However, the importance of ML-based feature analysis and selection is often...
Journal of chemical information and modeling
Feb 6, 2024
Structurally and conformationally diverse databases are needed to train accurate neural networks or kernel-based potentials capable of exploring the complex free energy landscape of flexible functional organic molecules. Curating such databases for s...