Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Improving tabular data extraction in scanned laboratory reports using deep learning models.

OBJECTIVE: Medical laboratory testing is essential in healthcare, providing crucial data for diagnos...

Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images.

Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical ind...

FluPMT: Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning.

Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the cons...

Building and testing of a robotic intervention framework to enhancing the social engagement of children with autism spectrum disorder.

PURPOSE: Humanoid robot intervention programmes for children with autism spectrum disorder (ASD) are...

DeepCOVIDNet-CXR: deep learning strategies for identifying COVID-19 on enhanced chest X-rays.

OBJECTIVES: COVID-19 is one of the recent major epidemics, which accelerates its mortality and preva...

Perceived Impact of COVID-19 in an Underserved Community: A Natural Language Processing Approach.

AIM: To utilise natural language processing (NLP) to analyse interviews about the impact of COVID-19...

Prediction of pathological complete response to chemotherapy for breast cancer using deep neural network with uncertainty quantification.

BACKGROUND: The I-SPY 2 trial is a national-wide, multi-institutional clinical trial designed to eva...

A novel mean shape based post-processing method for enhancing deep learning lower-limb muscle segmentation accuracy.

This study aims at improving the lower-limb muscle segmentation accuracy of deep learning approaches...

Two-stage deep learning framework for occlusal crown depth image generation.

The generation of depth images of occlusal dental crowns is complicated by the need for customizatio...

Peripheral Blood Mononuclear Cell Biomarkers for Major Depressive Disorder: A Transcriptomic Approach.

Major depressive disorder (MDD) is a complex condition characterized by persistent depressed mood, ...

Intelligent computing framework to analyze the transmission risk of COVID-19: Meyer wavelet artificial neural networks.

The optimum control methods for the epidemiology of the COVID-19 model are acknowledged using a nove...

AI-driven antibody design with generative diffusion models: current insights and future directions.

Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specifi...

Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.

Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of in...

Integrating machine learning to advance epitope mapping.

Identifying epitopes, or the segments of a protein that bind to antibodies, is critical for the deve...

Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.

BACKGROUNDS: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the dise...

MGA-Net: A novel mask-guided attention neural network for precision neonatal brain imaging.

In this study, we introduce MGA-Net, a novel mask-guided attention neural network, which extends the...

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning.

Computational models have made significant progress in predicting the effect of protein variants. Ho...

Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet.

To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined wit...

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