Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 271 to 280 of 157,320 articles

Confidence-Driven Deep Learning Framework for Early Detection of Knee Osteoarthritis.

IEEE transactions on bio-medical engineering
Knee Osteoarthritis (KOA) is a prevalent musculoskeletal disorder that severely impacts mobility and quality of life, particularly among older adults. Its diagnosis often relies on subjective assessments using the Kellgren-Lawrence (KL) grading syste...

Tora2: Motion and Appearance Customized Diffusion Transformer for Multi-Entity Video Generation

arXiv
Recent advances in diffusion transformer models for motion-guided video generation, such as Tora, have shown significant progress. In this paper, we present Tora2, an enhanced version of Tora, which introduces several design improvements to expand ...

PSAT: Pediatric Segmentation Approaches via Adult Augmentations and Transfer Learning

arXiv
Pediatric medical imaging presents unique challenges due to significant anatomical and developmental differences compared to adults. Direct application of segmentation models trained on adult data often yields suboptimal performance, particularly f...

Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study.

Journal of imaging informatics in medicine
Manually analyzing a series of MRI images to obtain information about the heart's motion is a time-consuming and labor-intensive task. Recently, many AI-driven tools have been used to automatically analyze cardiac MRI. However, it is still unknown wh...

R-VLM: Region-Aware Vision Language Model for Precise GUI Grounding

arXiv
Visual agent models for automating human activities on Graphical User Interfaces (GUIs) have emerged as a promising research direction, driven by advances in large Vision Language Models (VLMs). A critical challenge in GUI automation is the precise...

Bridging Perception and Language: A Systematic Benchmark for LVLMs' Understanding of Amodal Completion Reports

arXiv
One of the main objectives in developing large vision-language models (LVLMs) is to engineer systems that can assist humans with multimodal tasks, including interpreting descriptions of perceptual experiences. A central phenomenon in this context i...

Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks.

Scientific reports
Understanding the structural and operational characteristics of complex systems is crucial for network science research and analysis. To better understand the dynamics and behaviors of networks, it involves studying them in a variety of settings, inc...

CombiANT reader: Deep learning-based automatic image processing tool to robustly quantify antibiotic interactions.

PLOS digital health
Antibiotic resistance is a severe danger to human health, and combination therapy with several antibiotics has emerged as a viable treatment option for multi-resistant strains. CombiANT is a recently developed agar plate-based assay where three reser...

Simulation of emitter discharge along drip laterals under drip fertigation system using artificial neural network.

PloS one
Simulation of emitter discharge under a drip fertigation system is important for capturing the variation in water and nutrient distribution to crops. This is important for an effective design and irrigation management for agricultural crops. Moreover...

Enhancing diabetes risk prediction through focal active learning and machine learning models.

PloS one
To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based on focal active learning strategies combined with machine learning models. Existing machine learning models often suffer from poor performance on imbal...