Artificial Intelligence Medical Compendium

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

Showing 17,171 to 17,180 of 213,726 articles

Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis

arXiv
Designing realistic and functional 3D indoor rooms is essential for a wide range of applications, including interior design, virtual reality, gaming, and embodied AI. While recent MLLM-based approaches have shown great potential for 3D room synthesis... read more 

PERL: Parameter Efficient Reasoning in CLIP Latent Space

arXiv
Contrastively trained vision-language models such as CLIP provide strong zero-shot transfer by aligning images and text in a shared embedding space. However, adapting these models to downstream tasks without degrading their open-vocabulary generaliza... read more 

Speech-Guided Multimodal Learning for Vocal Tract Segmentation in Real-Time MRI

arXiv
Segmenting vocal tract articulators in real-time MRI (rtMRI) is a challenging dynamic image segmentation problem characterized by low contrast, rapid motion, and limited spatial resolution. However, while rtMRI acquisitions may provide synchronized a... read more 

Flowing with Confidence

arXiv
Generative models can produce nonsensical text, unrealistic images, and unstable materials faster than simulation or human review can absorb; without per-sample confidence, trust erodes. Existing fixes run $k$ ensembles or stochastic trajectories at ... read more 

Benchmarking transferability of SSL pretraining to same and different modality segmentation tasks

arXiv
Methods: Nine SSL methods spanning four pretext-task families were pretrained from scratch using the same 10{,}412 3D CT scans (1.89~M 2D axial slices) covering varied disease sites. The pretrained Swin Transformer encoder from each method was integr... read more 

Weakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation

arXiv
Due to the difficulty of obtaining ground-truth data for 4D radar scene flow estimation, previous methods typically rely on either self-supervised losses or cross-modal supervision using 3D LiDAR data, 2D images, and odometry. However, self-supervise... read more 

Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification

arXiv
In histopathology, human experts primarily rely on color as a means of enhancing contrast to interpret tissue morphology, whereas machine vision models process color as raw statistical information. This distinction raises a fundamental question: to w... read more 

PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference

arXiv
Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor continuous trajectories are observed, so the snapshot distributions alone do not uniquely determine the un... read more 

Lance: Unified Multimodal Modeling by Multi-Task Synergy

arXiv
We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather than relying on model capacity scaling or text-image-dominant designs, Lance explores a practical par... read more 

Can machine learning for quantum-gas experiments be explainable?

arXiv
Virtually all aspects of many-body atomic physics are challenging: experiments are technically demanding, datasets have become enormous, and the memory and CPU requirements for classical simulation of generic quantum systems often scale exponentially... read more