Latest AI and machine learning research in risk management for healthcare professionals.
Spatial relation questions require a model to identify the queried subject and object before comparing their layout. Yet a VLM can recognize both entities and still answer from the wrong instance or an ambiguous global view. We ask whether making query-specific evidence explicit can mitigate this failure and propose SEER (Self-grounded Evidence for Entity-Relation Reasoning), a training-free infer...
When decoder language models are used as classifiers, predicted class probabilities depend on implementation choices, including the prompt template, verbalizer (label-to-token mapping), and scoring rule, that are rarely treated as experimental variables. We present a controlled evaluation of three Mistral-7B variants (Base, BioMistral, and Instruct) on PubMed RCT sentence classification (n=2000) u...
Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear...
Captions serve as a primary supervision signal for both multimodal understanding and text-to-image generation. However, previous evaluations treat the...
Infrared-visible image fusion (IVIF) has no ideal fused reference, so fusion algorithms are routinely ranked by scalar objective metrics that formaliz...
Enterprise investment in generative artificial intelligence (AI) tripled in a single year to roughly US$37 billion, yet independent field research fin...
The zero-shot capabilities of multimodal large language models (MLLMs) are pushing salient object detection (SOD) beyond task-specific supervision. To...
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for breast cancer management, but reliance on gadolinium-based contrast ag...
As forecasts increasingly drive decisions in fields such as energy, transportation, and healthcare, understanding the historical data behind these pre...
We present HERMES (Hybrid Ensemble for Radiotherapy-target segmentation, Malignancy staging, and Event-free Survival), a single containerized algorith...
Brain tumors such as glioma, meningioma, and pituitary adenoma alter the mechanical behavior of soft brain tissue, yet common diagnostic methods rely ...
Statistical analysis on sensitive datasets like medical records and financial transactions is essential for decision-making, but raises significant pr...
Unmanned aerial vehicle (UAV)-satellite cross-view geo-localization matches UAV images against satellite imagery and has achieved impressive accuracy ...
Medical-imaging AI benchmarks combine datasets, DICOM rendering, prompts, provider APIs, automated labels, statistical code, manuscripts, and reposito...
Compressed short-text generators can fail in two different places: the codec may discard information before generation starts, or the latent generator...
Female pelvic diseases remain an under researched area characterized by often delayed diagnosis. While pelvic MRI offers superior soft-tissue contrast...
Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, ...
This paper introduces a new benchmark test, Medical-Checklist, for assessing medical multimodal models. The recent advancements in multimodal models h...
Spatial intelligence is essential for agents to move from static semantic understanding toward interacting with the physical world. Many spatial tasks...
While automated research systems promise to accelerate empirical analysis, they are prone to silent failures: instances in which analysis code execute...