COVID-19

AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia.

OBJECTIVE: To quantitatively evaluate computed tomography (CT) parameters of coronavirus disease 2019 (COVID-19) pneumonia an artificial intelligence (AI)-based software in different clinical severity groups during the disease course.

Thoughts on Objectives of Sparse and Hierarchical Masked Image Model

Masked image modeling is one of the most poplular objectives of training. Recently, the SparK model has been proposed with superior performance among self-supervised learning models. This paper proposes a new mask pattern for this SparK model, proposing it as the Mesh Mask-ed SparK model. We report the effect of the mask pattern used for image masking in pre-training on performance.

Improved Mixing of Critical Hardcore Model

The hardcore model is one of the most classic and widely studied examples of undirected graphical models. Given a graph $G$, the hardcore model desc...

Geometric Prior-Guided Neural Implicit Surface Reconstruction in the Wild

Neural implicit surface reconstruction using volume rendering techniques has recently achieved significant advancements in creating high-fidelity su...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae famil...

EVOLVE: A Web Platform for AI-Based Protein Mutation Prediction and Evolutionary Phase Exploration.

While predicting structure-function relationships from sequence data is fundamental in biophysical chemistry, identifying prospective single-point and...

Impact of canny edge detection preprocessing on performance of machine learning models for Parkinson's disease classification.

This study investigates the classification of individuals as healthy or at risk of Parkinson's disease using machine learning (ML) models, focusing on...

High-Frequency Prior-Driven Adaptive Masking for Accelerating Image Super-Resolution

The primary challenge in accelerating image super-resolution lies in reducing computation while maintaining performance and adaptability. Motivated ...

Missing Data Estimation for MR Spectroscopic Imaging via Mask-Free Deep Learning Methods

Magnetic Resonance Spectroscopic Imaging (MRSI) is a powerful tool for non-invasive mapping of brain metabolites, providing critical insights into n...

Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemic disease defined by a suite of symptoms, includin...

A scalable deep attention mechanism of instance segmentation for the investigation of chromosome.

Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and genomics due to the inherent complexity, variabilit...

Application of in-silico approaches in subunit vaccines: Overcoming the challenges of antigen and adjuvant development.

Subunit vaccines are crucial in preventing modern diseases due to their safety, stability, and ability to elicit targeted immune responses. However, c...

Climate change prediction in Saudi Arabia using a CNN GRU LSTM hybrid deep learning model in al Qassim region.

Climate change, which causes long-term temperature and weather changes, threatens natural ecosystems and cities. It has worldwide economic consequence...

A new deep learning-based fast transcoding for internet of things applications.

To achieve low-power video communication in Internet of Things, this study presents a new deep learning-based fast transcoding algorithm from distribu...

Electrocardiographic diagnostic possibilities for atrial fibrillation using artificial intelligence: Differentiation from sinus rhythm and other arrhythmias with the PMcardio app in COVID-19 patients.

BACKGROUND: Artificial intelligence (AI) has shown potential in enhancing ECG analysis, but its accuracy in detecting atrial fibrillation (AF) in COVI...

Dendritic cell-based microrobots for enhanced systemic antigen-specific immune tolerance.

Current immunotherapeutic approaches for autoimmune disorders primarily rely on the use of generalized immunosuppressive medications. However, most im...

Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) is a novel predictive biomarker for chemotherapy and immunotherapy response, as well as prognostic indicat...

FastDup: a scalable duplicate marking tool using speculation-and-test mechanism

Duplicate marking is a critical preprocessing step in gene sequence analysis to flag redundant reads arising from polymerase chain reaction(PCR) amp...

Noise-Consistent Siamese-Diffusion for Medical Image Synthesis and Segmentation

Deep learning has revolutionized medical image segmentation, yet its full potential remains constrained by the paucity of annotated datasets. While ...

Achieving 3D Attention via Triplet Squeeze and Excitation Block

The emergence of ConvNeXt and its variants has reaffirmed the conceptual and structural suitability of CNN-based models for vision tasks, re-establi...