COVID-19

An Intelligent Model of Segmentation and Classification Using Enhanced Optimization-Based Attentive Mask RCNN and Recurrent MobileNet With LSTM for Multiple Sclerosis Types With Clinical Brain MRI.

In healthcare sector, magnetic resonance imaging (MRI) images are taken for multiple sclerosis (MS) assessment, classification, and management. However, interpreting an MRI scan requires an exceptional amount of skill because abnormalities on scans are frequently inconsistent with clinical symptoms, making it difficult to convert the findings into effective treatment strategies. Furthermore, MRI i...

An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net.

Quantitative susceptibility mapping (QSM) provides the spatial distribution of magnetic susceptibility within tissues through sequential steps: phase unwrapping and echo combination, mask generation, background field removal, and dipole inversion. Accurate mask generation is crucial, as masks excluding regions outside the brain and without holes are necessary to minimize errors and streaking artif...

Advancing label-free cell classification with connectome-inspired explainable models and a novel LIVECell-CLS dataset.

Deep learning label-free cell imaging has become essential in modern medical applications, enabling precise cell analysis while preserving natural bio...

Research on the influencing factors of PM in China at different spatial scales based on machine learning algorithm.

PM pollution is one of the prominent environmental issues currently faced in China, influenced by various factors and showed significant spatial diffe...

Improved prediction of chlorophyll-a concentrations using advancing graph neural network variants.

Accurate estimation of harmful algal blooms is essential for protecting surface water. Chlorophyll-a (Chl-a), commonly used as a proxy for estimating ...

Improved surface NO Retrieval: Double-layer machine learning model construction and spatio-temporal characterization analysis in China (2018-2023).

As an important atmospheric pollutant causing serious harm to human health and the natural environment, monitoring of surface NO (SNO) level is of cri...

Digenic variant interpretation with hypothesis-driven explainable AI.

The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately in...

Assessing amyloid fibrils and amorphous aggregates: A review.

Protein misfolding and aggregation play a central role in the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's. These agg...

Seg2Any: Open-set Segmentation-Mask-to-Image Generation with Precise Shape and Semantic Control

Despite recent advances in diffusion models, top-tier text-to-image (T2I) models still struggle to achieve precise spatial layout control, i.e. accu...

Towards Graph-Based Privacy-Preserving Federated Learning: ModelNet -- A ResNet-based Model Classification Dataset

Federated Learning (FL) has emerged as a powerful paradigm for training machine learning models across distributed data sources while preserving dat...

Efficient Endangered Deer Species Monitoring with UAV Aerial Imagery and Deep Learning

This paper examines the use of Unmanned Aerial Vehicles (UAVs) and deep learning for detecting endangered deer species in their natural habitats. As...

Diffusion-Based Symbolic Regression

Diffusion has emerged as a powerful framework for generative modeling, achieving remarkable success in applications such as image and audio synthesi...

TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matching

Tumor data synthesis offers a promising solution to the shortage of annotated medical datasets. However, current approaches either limit tumor diver...

Methylomes Reveal Recent Evolutionary Changes in Populations of Two Plant Species.

Plant DNA methylation changes occur hundreds to thousands of times faster than DNA mutations and can be transmitted transgenerationally, making them u...

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration

Precision agriculture requires efficient autonomous systems for crop monitoring, where agents must explore large-scale environments while minimizing...

Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models

Enhancing the reasoning capabilities of large language models effectively using reinforcement learning (RL) remains a crucial challenge. Existing ap...

Score-based Generative Modeling for Conditional Independence Testing

Determining conditional independence (CI) relationships between random variables is a fundamental yet challenging task in machine learning and stati...

DeepRTE: Pre-trained Attention-based Neural Network for Radiative Tranfer

In this paper, we propose a novel neural network approach, termed DeepRTE, to address the steady-state Radiative Transfer Equation (RTE). The RTE is...

MMGT: Motion Mask Guided Two-Stage Network for Co-Speech Gesture Video Generation

Co-Speech Gesture Video Generation aims to generate vivid speech videos from audio-driven still images, which is challenging due to the diversity of...

Second Opinion Matters: Towards Adaptive Clinical AI via the Consensus of Expert Model Ensemble

Despite the growing clinical adoption of large language models (LLMs), current approaches heavily rely on single model architectures. To overcome ri...