Latest AI and machine learning research in surveys for healthcare professionals.
Cross-view feature matching aims to establish reliable correspondences across images with large viewpoint variations. Over the past decade, the field has evolved from task-specific models toward increasingly unified and generalizable correspondence models, with recent progress further driven by the emergence of vision foundation models (VFMs). Despite these advances, existing studies remain highly...
Conditional Independence (CI) tests are the statistical engine of constraint-based causal discovery: in algorithms such as PC (Peter-Clark) and FCI (Fast Causal Inference), skeleton pruning and key orientations follow directly from CI decisions. This survey reviews CI testing with emphasis on assumptions, robustness, and scalability in high-dimensional and mixed-type settings common in biomedical ...
Large Language Models (LLMs) have achieved strong performance in medical question answering and clinical reasoning tasks. However, their reliability u...
Wireless Body Area Networks (WBANs) generate multivariate physiological time series that are highly nonstationary and must often be processed under st...
Multi-stage boundary representation (B-Rep) generation leverages intermediate wireframes to synthesize CAD models. However, geometric and topological ...
Translating natural language instructions into machine-interpretable formal specifications enables robots and autonomous systems to plan, reason, and ...
Accurate six-degree-of-freedom (6-DOF) motion estimation is essential for robotic manipulation, autonomous systems, and structural displacement monito...
Standard accuracy metrics for VLMs often mask significant reliability failures in sensitive domains. In this work, we utilize a histopathology-validat...
Multi-stage boundary representation (B-Rep) generation leverages intermediate wireframes to synthesize CAD models. However, geometric and topological ...
Emergency triage requires reliable decisions within a short time period. However, the available electronic health record (EHR) data, including structu...
Cardiac digital twins convert clinical images into physiological measurements through observation operators, yet calibration studies often assume a fi...
Text-to-image (T2I) generation models are increasingly embedded in applications such as media content creation and education, raising concerns about h...
In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local cont...
Rapid advances in image generation models call for interpretable AI-generated image detection methods that not only determine authenticity but also pr...
Traffic police gestures are safety-critical perception cues for autonomous driving. A deployable recognizer must infer commands causally from continuo...
Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning systems into high-stakes domains such as digital he...
Existing astronomy foundation models provide strong galaxy representations, but adapting them to new survey conditions and survey-specific morphology ...
Aerial-ground person re-identification is a challenging task due to cross-platform viewpoint variations, which cause severe occlusion and geometric de...
RGB imagery offers a practical, low-cost option for Unmanned Aerial/Ground Vehicle (UAV/UGV) survey support in surface-landmine detection, but object ...
Structure-based scoring functions leveraging machine learning have recently demonstrated superior performance over classical scoring functions, partic...