Neurology

Head Trauma

Latest AI and machine learning research in head trauma for healthcare professionals.

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Post-Transplant Liver Monitoring Utilizing Integrated Surface-Enhanced Raman and AI in Hepatic Ischemia-Reperfusion Injury Animal Model.

BACKGROUND: While liver transplantation saves lives from irreversible liver damage, it poses challen...

Jan 2025 40452789
Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.

CONTEXT AND BACKGROUND: Depression has affected millions of people worldwide and has become one of t...

Jan 2025 40435349
AntBot-EX: Enhancing robot search efficiency in complex post-disaster environments.

In post-disaster scenarios, effective rescue operations hinge on deploying robots equipped with soph...

Jan 2025 40402955
Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial ...

Jan 2025 40036109
PQD: Post-training Quantization for Efficient Diffusion Models

Diffusionmodels(DMs)havedemonstratedremarkableachievements in synthesizing images of high fidelity...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, mak...

Dec 2024 40000199
Accelerating Post-Tornado Disaster Assessment Using Advanced Deep Learning Models

Post-disaster assessments of buildings and infrastructure are crucial for both immediate recovery ...

Neuromorphic Spiking Neural Network Based Classification of COVID-19 Spike Sequences

The availability of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus data post-C...

Progressive Fine-to-Coarse Reconstruction for Accurate Low-Bit Post-Training Quantization in Vision Transformers

Due to its efficiency, Post-Training Quantization (PTQ) has been widely adopted for compressing Vi...

I0T: Embedding Standardization Method Towards Zero Modality Gap

Contrastive Language-Image Pretraining (CLIP) enables zero-shot inference in downstream tasks such...

Sentiment and Hashtag-aware Attentive Deep Neural Network for Multimodal Post Popularity Prediction

Social media users articulate their opinions on a broad spectrum of subjects and share their exper...

Three-in-One: Robust Enhanced Universal Transferable Anti-Facial Retrieval in Online Social Networks

Deep hash-based retrieval techniques are widely used in facial retrieval systems to improve the ef...

Unified HT-CNNs Architecture: Transfer Learning for Segmenting Diverse Brain Tumors in MRI from Gliomas to Pediatric Tumors

Accurate segmentation of brain tumors from 3D multimodal MRI is vital for diagnosis and treatment ...

Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical imp...

A Pipeline and NIR-Enhanced Dataset for Parking Lot Segmentation

Discussions of minimum parking requirement policies often include maps of parking lots, which are ...

Leveraging Audio and Text Modalities in Mental Health: A Study of LLMs Performance

Mental health disorders are increasingly prevalent worldwide, creating an urgent need for innovati...

Take Fake as Real: Realistic-like Robust Black-box Adversarial Attack to Evade AIGC Detection

The security of AI-generated content (AIGC) detection is crucial for ensuring multimedia content c...

Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation

Accurate and automatic segmentation of brain tumors in multi-parametric magnetic resonance imaging...

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