Universal precautions

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 different parts of the body in terms of amplitude of motion, audio relevance, and detailed features. Relying solely on audio as the control signal often fails to capture large gesture movements in video, leading to more pronounced artifacts and dist...

Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic strategies. This study aims to elucidate the roles of miR-223-3p and CRIM1 in HBV-MN using single-cell RNA sequencing (scRNA-seq) and machine learning...

Adapting Segment Anything Model for Power Transmission Corridor Hazard Segmentation

Power transmission corridor hazard segmentation (PTCHS) aims to separate transmission equipment and surrounding hazards from complex background, con...

Concentrate on Weakness: Mining Hard Prototypes for Few-Shot Medical Image Segmentation

Few-Shot Medical Image Segmentation (FSMIS) has been widely used to train a model that can perform segmentation from only a few annotated images. Ho...

Scalable and robust machine learning framework for HIV classification using clinical and laboratory data.

Human Immunodeficiency Virus (HIV) is a retrovirus that weakens the immune system, increasing vulnerability to infections and cancers. HIV spreads pri...

OmniSync: Towards Universal Lip Synchronization via Diffusion Transformers

Lip synchronization is the task of aligning a speaker's lip movements in video with corresponding speech audio, and it is essential for creating rea...

InstGenIE: Generative Image Editing Made Efficient with Mask-aware Caching and Scheduling

Generative image editing using diffusion models has become a prevalent application in today's AI cloud services. In production environments, image e...

Sarcopenia and frailty: An in-depth analysis of the pathophysiology and effect on liver transplant candidates.

Cirrhosis represents the end stage of chronic liver disease, significantly reducing life expectancy as it progresses from a compensated to a decompens...

MotionPro: A Precise Motion Controller for Image-to-Video Generation

Animating images with interactive motion control has garnered popularity for image-to-video (I2V) generation. Modern approaches typically rely on la...

The Missing Point in Vision Transformers for Universal Image Segmentation

Image segmentation remains a challenging task in computer vision, demanding robust mask generation and precise classification. Recent mask-based app...

Machine Learning of Molecular Dynamics Simulations Provides Insights into the Modulation of Viral Capsid Assembly.

An effective approach in the development of novel antivirals is to target the assembly of viral capsids by using capsid assembly modulators (CAMs). CA...

ThinkVideo: High-Quality Reasoning Video Segmentation with Chain of Thoughts

Reasoning Video Object Segmentation is a challenging task, which generates a mask sequence from an input video and an implicit, complex text query. ...

Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation

Open-set image segmentation poses a significant challenge because existing methods often demand extensive training or fine-tuning and generally stru...

SynRES: Towards Referring Expression Segmentation in the Wild via Synthetic Data

Despite the advances in Referring Expression Segmentation (RES) benchmarks, their evaluation protocols remain constrained, primarily focusing on eit...

Instruct2See: Learning to Remove Any Obstructions Across Distributions

Images are often obstructed by various obstacles due to capture limitations, hindering the observation of objects of interest. Most existing methods...

A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective.

BACKGROUND: Hepatitis B virus (HBV) can be transmitted from mother to child either through transplacental infection or via blood-to-blood contact duri...

Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding

Recent advancements in multimodal large language models (MLLMs) have significantly improved performance in visual question answering. However, they ...

Explainable embeddings with Distance Explainer

While eXplainable AI (XAI) has advanced significantly, few methods address interpretability in embedded vector spaces where dimensions represent com...

Development of a machine learning prediction model for loss to follow-up in HIV care using routine electronic medical records in a low-resource setting.

BACKGROUND: Despite the global commitment to ending AIDS by 2030, the loss of follow-up (LTFU) in HIV care remains a significant challenge. To address...

Classification of disease subtypes in medical spectroscopy for multi-category sample imbalances based on grouping and hierarchical learning.

In the medical domain, the challenges in sample acquisition and collection often result in imbalanced training sets for multi-class models, especially...