Latest AI and machine learning research in alternative medicine for healthcare professionals.
Multimodal large language models (MLLMs) achieve strong performance on benchmarks that evaluate text...
With the emergence of search-enabled generative QA systems, users are increasingly turning to tools ...
Background: Artificial intelligence chatbots (AICs) are increasingly being integrated into scholarly...
Mapping is crucial in robotics for localization and downstream decision-making. As robots are deploy...
Multimodal Image Fusion (MMIF) integrates complementary information from various modalities to produ...
Cross-view geo-localization (CVGL) aims to establish spatial correspondences between images captured...
Classical radiomic features are designed to quantify image appearance and intensity patterns. Compar...
Clinicians commonly interpret three-dimensional (3D) medical images, such as computed tomography (CT...
Background: Biomedical Large Language Models (LLMs) combined with prompt engineering offer domain-sp...
Deep learning models for medical image analysis often act as black boxes, seldom aligning with clini...
Radiomics and deep learning both offer powerful tools for quantitative medical imaging, but most exi...
Multimodal Fusion Learning (MFL), leveraging disparate data from various imaging modalities (e.g., M...
Precision medicine requires models that can translate rich molecular measurements into individualize...
Deep learning has achieved expert-level performance in automated electrocardiogram (ECG) diagnosis, ...
Histone modifications underpin the cell-type-specific gene regulatory networks that drive the remark...
Existing cross-modal pedestrian detection (CMPD) employs complementary information from RGB and ther...
This study explores the integration of multiple Explainable AI (XAI) techniques to enhance the inter...
Multimodal learning aims to integrate complementary information from heterogeneous modalities, yet s...
Accurate prediction of drug response in precision medicine requires models that capture how specific...
Zero-shot composed image retrieval (ZS-CIR) is a rapidly growing area with significant practical app...
In this study, we explore the application of deep learning techniques for predicting cleansing quali...