Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the...
Current breast cancer diagnosis methods often face limitations such as high cost, time consumption, and inter-observer variability. To address these challenges, this research proposes a novel deep learning framework that leverages generative adversar...
A neural network was trained to generate synthetic images of severe and moderate psoriatic plaques, after being trained on 375 photographs of patients with psoriasis taken in a clinical setting. A latent w-space vector was identified that allowed the...
Emotion recognition in social media is a challenging task due to the complex and unstructured nature of user-generated content. In this paper, we propose Emotion-RGC Net, a novel deep learning model that integrates RoBERTa, Graph Neural Networks (GNN...
International journal of laboratory hematology
Mar 2, 2025
INTRODUCTION: Von Willebrand factor (VWF) multimer analysis is essential for diagnosing and classifying von Willebrand disease (VWD) but requires expert interpretation and is subject to inter-rater variability. We developed an automated image analysi...
BACKGROUND: To develop and validate a model that integrates clinical data, deep learning radiomics, and radiomic features to predict high-risk patients for cage subsidence (CS) after lumbar fusion.
INTRODUCTION: Pesticides play a pivotal role in ensuring food security, and the development of green pesticides is an inevitable trend in global agricultural progress. Although deep learning-based generative models have revolutionized de novo drug de...
BACKGROUND: Deep learning (DL) has been shown to be successful in interpreting radiographs and aiding in fracture detection and classification. However, no study has aimed to develop a computer vision model for tibia plateau fractures using the Schat...
Clinical oncology (Royal College of Radiologists (Great Britain))
Mar 1, 2025
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).
This study introduces an AI-derived pain sign for continuous neonatal pain assessment, addressing the limitations of existing pain scales and computational approaches. Traditional pain scales, though widely used, are hindered by inter-rater variabili...
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