Alternative Medicine

A novel hybrid vision UNet architecture for brain tumor segmentation and classification.

This paper focuses on designing and developing novel architectures termed Hybrid Vision UNet-Encoder Decoder (HVU-ED) segmenter and Hybrid Vision UNet-Encoder (HVU-E) classifier for brain tumor segmentation and classification, respectively. The proposed model integrates the powerful feature extraction capabilities of hybrid methods like ResNet50, VGG16, Dense121 and Xception with Vision Transforme...

Listening deeper: neural networks unravel acoustic features in preterm infant crying.

Early infant crying provides critical insights into neurodevelopment, with atypical acoustic features linked to conditions such as preterm birth. However, previous studies have focused on limited and specific acoustic features, hindering a more comprehensive understanding of crying. To address this, we employed a convolutional neural network to assess whether whole Mel-spectrograms of infant cryin...

Understanding dimensions of trust in AI through quantitative cognition: Implications for human-AI collaboration.

Human-AI collaborative innovation relies on effective and clearly defined role allocation, yet empirical research in this area remains limited. To add...

Design of a deep fusion model for early Parkinson's disease prediction using handwritten image analysis.

Parkinson's Disease (PD) is a deteriorating condition that mostly affects older people. The lack of conclusive treatment for PD makes diagnosis very c...

Hierarchical cross attention achieves pixel precise landslide segmentation in submeter optical imagery.

Accurate landslide segmentation using remote sensing imagery is a critical component of geohazards response systems, particularly in time-sensitive ta...

Inducing Neural Collapse via Anticlasses and One-Cold Cross-Entropy Loss.

While softmax cross-entropy (CE) loss is the standard objective for supervised classification, it primarily focuses on the ground-truth classes, ignor...

Exploring semantic grounding in the posterior parietal cortex.

This study examines the evolving perspective on semantic processing, which has shifted from the traditional view of an isolated semantic memory system...

From traditional medicine to modern medicine: the importance of TCM regulatory science (TCMRS) as an emerging discipline.

Traditional Chinese medicine (TCM) has become a standardized medical system through systematic development across global healthcare practices. However...

Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors enable the collection of multiple health modalities from many individuals. Access to mult...

Examining the biological causes of eating disorders to inform treatment strategies.

Despite their prevalence, eating disorders (EDs) are under-researched and often misunderstood. A recent focus of research on the biological underpinni...

Robotic-assisted gait training for spinal cord injury neuropathic pain: A systematic review.

CONTEXT: Neuropathic pain (NP), can be a debilitating consequence of spinal cord injury. Robotic-assisted gait training (RAGT) is an effective rehabil...

Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms.

Prenatal healthcare development requires accurate automated techniques for fetal ultrasound image segmentation. This approach allows standardized eval...

Mulberry leaf disease detection by CNN-ViT with XAI integration.

Mulberry leaf disease detection is vital for maintaining the health and productivity of mulberry crops. In this paper, a novel approach was proposed b...

Deep Learning Black-Box and Pattern Recognition Analysis Using Guided Grad-CAM for Phytolith Identification.

BACKGROUND AND AIMS: In this article, visual explainers are applied to give transparency to the black-box of a trained VGG19 model for the identificat...

Integrative transcriptomics and single-cell transcriptomics analyses reveal potential biomarkers and mechanisms of action in papillary thyroid carcinoma.

OBJECTIVE: Papillary thyroid carcinoma (PTC) has a high recurrence rate and lacks reliable diagnostic biomarkers. This study aims to identify robust t...

Macrophage histone lactylation in atherosclerosis progression: mechanisms, predictive models, and therapeutic potential of Ruan Jian Qing Mai formula.

AIMS: This study investigates the role of macrophage histone lactylation-a protein modification-in atherosclerosis progression, particularly in periph...

A Multi‑Region Brain Model to Elucidate the Role of Hippocampus in Spatially Embedded Decision‑Making.

Brains excel at robust decision-making and data-efficient learning. Understanding the architectures and dynamics underlying these capabilities can inf...

An integrative and comprehensive analysis of blood transcriptomes combined with machine learning models reveals key signatures for tuberculosis diagnosis and risk stratification.

Tuberculosis (TB) remains a major global health challenge, contributing substantially to morbidity and mortality worldwide. The progression from (Mtb...

Mitigating patient harm risks: A proposal of requirements for AI in healthcare.

With the rise Artificial Intelligence (AI), mitigation strategies may be needed to integrate AI-enabled medical software responsibly, ensuring ethical...

Brassica microgreens shape gut microbiota and functional metabolite profiles in a species-related manner: A multi-omics approach following in vitro gastrointestinal digestion and large intestine fermentation.

Brassicaceae microgreens constitute a novel and promising source of bioactive compounds, such as polyphenols and glucosinolates. In this work, an inte...