Alternative Medicine

Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection

RGB-Thermal Salient Object Detection aims to pinpoint prominent objects within aligned pairs of visible and thermal infrared images. Traditional encoder-decoder architectures, while designed for cross-modality feature interactions, may not have adequately considered the robustness against noise originating from defective modalities. Inspired by hierarchical human visual systems, we propose the C...

Class Distance Weighted Cross Entropy Loss for Classification of Disease Severity

Assessing disease severity with ordinal classes, where each class reflects increasing severity levels, benefits from loss functions designed for this ordinal structure. Traditional categorical loss functions, like Cross-Entropy (CE), often perform suboptimally in these scenarios. To address this, we propose a novel loss function, Class Distance Weighted Cross-Entropy (CDW-CE), which penalizes mi...

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

Explainable Artificial Intelligence (XAI) addresses the growing need for transparency and interpretability in AI systems, enabling trust and account...

Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) involves complex compatibility mechanisms characterized by multi-component and multi-target interactions, which a...

Relation extraction using large language models: a case study on acupuncture point locations.

OBJECTIVE: In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabili...

Exploring prognostic biomarkers in pathological images of colorectal cancer patients via deep learning.

Hematoxylin and eosin (H&E) whole slide images provide valuable information for predicting prognostic outcomes in colorectal cancer (CRC) patients. Ho...

Y-AR: A Mixed Reality CAD Tool for 3D Wire Bending

Wire bending is a technique used in manufacturing to mass-produce items such as clips, mounts, and braces. Wire bending machines like the DIWire by ...

Multimodal Alignment of Histopathological Images Using Cell Segmentation and Point Set Matching for Integrative Cancer Analysis

Histopathological imaging is vital for cancer research and clinical practice, with multiplexed Immunofluorescence (MxIF) and Hematoxylin and Eosin (...

Understanding Clinical Decision-Making in Traditional East Asian Medicine through Dimensionality Reduction: An Empirical Investigation

This study examines the clinical decision-making processes in Traditional East Asian Medicine (TEAM) by reinterpreting pattern identification (PI) t...

Triangulating evidence in health sciences with Annotated Semantic Queries.

MOTIVATION: Integrating information from data sources representing different study designs has the potential to strengthen evidence in population heal...

Automatic Classification of Wound Images Showing Healing Complications: Towards an Optimised Approach for Detecting Maceration.

This study aims to advance the field of digital wound care by developing and evaluating convolutional neural network (CNN) architectures for the autom...

Learning from the few: Fine-grained approach to pediatric wrist pathology recognition on a limited dataset

Wrist pathologies, {particularly fractures common among children and adolescents}, present a critical diagnostic challenge. While X-ray imaging rema...

Interpretable breast cancer classification using CNNs on mammographic images

Deep learning models have achieved promising results in breast cancer classification, yet their 'black-box' nature raises interpretability concerns....

Automatic Feature Recognition and Dimensional Attributes Extraction From CAD Models for Hybrid Additive-Subtractive Manufacturing

The integration of Computer-Aided Design (CAD), Computer-Aided Process Planning (CAPP), and Computer-Aided Manufacturing (CAM) plays a crucial role ...

Breaking the Global North Stereotype: A Global South-centric Benchmark Dataset for Auditing and Mitigating Biases in Facial Recognition Systems

Facial Recognition Systems (FRSs) are being developed and deployed globally at unprecedented rates. Most platforms are designed in a limited set of ...

NeuroBind: Towards Unified Multimodal Representations for Neural Signals

Understanding neural activity and information representation is crucial for advancing knowledge of brain function and cognition. Neural activity, me...

EMIF: Evidence-aware Multi-source Information Fusion Network for Explainable Fake News Detection

Extensive research on automatic fake news detection has been conducted due to the significant detrimental effects of fake news proliferation. Most e...

Explainable Multimodal Deep Learning for Heart Sounds and Electrocardiogram Classification.

We introduce a Gradient-weighted Class Activation Mapping (Grad-CAM) methodology to assess the performance of five distinct models for binary classifi...

Human-AI collectives produce the most accurate differential diagnoses

Artificial intelligence systems, particularly large language models (LLMs), are increasingly being employed in high-stakes decisions that impact bot...

Deep-Learning Approach for Tissue Classification using Acoustic Waves during Ablation with an Er:YAG Laser (Updated)

Today's mechanical tools for bone cutting (osteotomy) cause mechanical trauma that prolongs the healing process. Medical device manufacturers aim to...