Learning more about events from the past can help make sense of current circumstances and inform the future. Equipping ...

This back-to-school season, the conversation is not just about devices or apps, but about how technology and innovation ...

Deep learning model deploy with Django Executive Summary This project is a Django-REST API that offers the consumption of a deep learning model using a simple front end. The model adopted in this work ...

Reply to: “Baseline Brain Metastasis Imbalance in TRUST: Implications for Interpreting Intracranial Efficacy of Taletrectinib” and “Taletrectinib in ROS1 Fusion–Positive Non–Small Cell Lung Cancer: ...

Methods A multimodal deep-learning model with transformers was developed for real-time recurrence prediction using baseline clinical, pathological, and molecular data with longitudinal laboratory and ...

Deep learning-based recommender systems are widely utilised in domains such as e-commerce. Yet there are limited studies that explore recommendation systems for expert and speciality needs such as ...

This study investigates the robustness of deep learning-based steganalysis models against common image transformations because most literature has not paid enough attention to resilience assessment.

Objective: To develop a deep learning (DL) model for carotid plaque detection based on CTA images and evaluate the clinical application feasibility and value of the model. Methods: We retrospectively ...

This research introduces a novel deep learning model based on OMT and multimode tensor SVD to predict molecular markers using international multicenter datasets. Our approach efficiently compresses ...