COVID-19

CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and Optimization

Target-specific peptides, such as conotoxins, exhibit exceptional binding affinity and selectivity toward ion channels and receptors. However, their therapeutic potential remains underutilized due to the limited diversity of natural variants and the labor-intensive nature of traditional optimization strategies. Here, we present CreoPep, a deep learning-based conditional generative framework that...

Grasp the Graph (GtG) 2.0: Ensemble of GNNs for High-Precision Grasp Pose Detection in Clutter

Grasp pose detection in cluttered, real-world environments remains a significant challenge due to noisy and incomplete sensory data combined with complex object geometries. This paper introduces Grasp the Graph 2.0 (GtG 2.0) method, a lightweight yet highly effective hypothesis-and-test robotics grasping framework which leverages an ensemble of Graph Neural Networks for efficient geometric reaso...

A comprehensive framework for statistical testing of brain dynamics

We introduce a comprehensive statistical framework for analysing brain dynamics and testing their associations with behavioural, physiological and o...

TeDA: Boosting Vision-Lanuage Models for Zero-Shot 3D Object Retrieval via Testing-time Distribution Alignment

Learning discriminative 3D representations that generalize well to unknown testing categories is an emerging requirement for many real-world 3D appl...

DNAZEN: Enhanced Gene Sequence Representations via Mixed Granularities of Coding Units

Genome modeling conventionally treats gene sequence as a language, reflecting its structured motifs and long-range dependencies analogous to linguis...

MaskClip: Detachable Clip-on Piezoelectric Sensing of Mask Surface Vibrations for Real-time Noise-Robust Speech Input

Masks are essential in medical settings and during infectious outbreaks but significantly impair speech communication, especially in environments wi...

ADCNet: a unified framework for predicting the activity of antibody-drug conjugates.

Antibody-drug conjugates (ADCs) have revolutionized the field of cancer treatment in the era of precision medicine due to their ability to precisely t...

Edge-preserving Image Denoising via Multi-scale Adaptive Statistical Independence Testing

Edge detection is crucial in image processing, but existing methods often produce overly detailed edge maps, affecting clarity. Fixed-window statist...

Enhancing Realism in Holographic Augmented Reality Displays through Occlusion Handling

In this paper, an occlusion-capable holographic augmented-reality (AR) display is proposed, and its ability to enhance AR imagery through occlusion ...

Current Diagnosing Strategies for Mycobacterium tuberculosis and its Drug Resistance: A Review.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains a major global health threat, compounded by the rise of extensively drug-resist...

Multivariate Conformal Selection

Selecting high-quality candidates from large datasets is critical in applications such as drug discovery, precision medicine, and alignment of large...

A Robust Deep Networks based Multi-Object MultiCamera Tracking System for City Scale Traffic

Vision sensors are becoming more important in Intelligent Transportation Systems (ITS) for traffic monitoring, management, and optimization as the n...

Perceptual Implications of Automatic Anonymization in Pathological Speech

Automatic anonymization techniques are essential for ethical sharing of pathological speech data, yet their perceptual consequences remain understud...

Fine-grained spatial-temporal perception for gas leak segmentation

Gas leaks pose significant risks to human health and the environment. Despite long-standing concerns, there are limited methods that can efficiently...

Deep Learning-based Anatomy-Aware Morph Model for Registration of Prostate Whole-Mount Histopathology to MRI.

Purpose To develop and evaluate a novel deep learning-based approach for registering presurgical MR and whole-mount histopathology (WMHP) images of th...

Predicting Recurrence in Locally Advanced Rectal Cancer Using Multitask Deep Learning and Multimodal MRI.

Purpose To develop and validate a deep multitask network, MultiRecNet, for fully automatic prediction of disease-free survival (DFS) in patients with ...

RLEAAI: improving antibody-antigen interaction prediction using protein language model and sequence order information.

Antibody-antigen interactions (AAIs) are a pervasive phenomenon in the natural and are instrumental in the design of antibody-based drugs. Despite the...

Machine Learning Analysis of Single-Voxel Proton MR Spectroscopy for Differentiating Solitary Fibrous Tumors and Meningiomas.

Solitary fibrous tumor (SFT), formerly known as hemangiopericytoma, is an uncommon brain tumor often confused with meningioma on MRI. Unlike meningiom...

Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework.

Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and automatic molecular subtype classification in breas...

Evaluating prostate cancer diagnostic methods: The role and relevance of digital rectal examination in modern era.

This review examines diagnostic methods for prostate cancer, focusing on the role of digital rectal examination (DRE) alongside modern advancements li...