Latest AI and machine learning research in health policy for healthcare professionals.
The Segment Anything Model 2 (SAM2) has advanced temporal promptable segmentation, yet its deployment remains hindered by heavy memory cross-attention overhead and redundant full-frame visual feature extraction. While recent methods explore efficiency via heuristic memory pruning and window-based sparse routing, they typically suffer from catastrophic performance degradation in complex segmentatio...
Large vision-language models (LVLMs) have recently shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judgments and interpretable defect reasoning. However, current LVLM-based IAD methods still struggle to produce precise pixel-level anomaly maps from generated language judgments. We aim to achieve precise pixel-level localization while using language as...
Long-document multimodal question answering requires more than retrieving relevant chunks from a large document. Different queries require different e...
Air pollution and climate-related stressors are increasingly important concerns for respiratory health, especially in settings with unequal environmen...
This study focuses on the relationship between access to Advanced Neonatal Care (ANC) and fertility across the regions in Ghana between 1988 and 2022....
The cost of healthcare remains a concern in the United States and may have been influenced by disruptions associated with the COVID-19 pandemic. This ...
Methods INCA is a prospective, single-center cohort study with nationwide recruitment. Participation is open to adult patients and informal caregivers...
On-policy distillation (OPD) has become a key paradigm in LLM post-training, yet its training dynamics remain poorly understood. We present a systemat...
Objectives: Natural language processing (NLP) can enable scalable extraction of clinically relevant information from unstructured radiology reports re...
The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatia...
Existing evaluations of healthcare AI often treat interoperability as a technical infrastructure issue rather than a factor that directly influences t...
Background Gestational diabetes mellitus (GDM) affects 1-in-7 pregnancies globally and is associated with significant short- and long-term health cons...
Agentic research systems are emerging as a new paradigm for coordinating scientific workflows beyond isolated model inference, code generation, or sta...
Spatial football metrics such as pitch control assume access to the positions of all 22 players, yet the most widely available source of positional da...
Designing cost functions of adaptive steganography traditionally requires extensive manual tuning, while deep learning methods lack interpretability. ...
Sri Lanka has experienced a decade of progressive forest degradation and rising atmospheric pollution, yet district-level respiratory admissions have ...
3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D re...
We study timestep allocation for score-based diffusion sampling, where a learned reverse-time dynamics is discretized on a finite grid. Uniform and ha...
On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to referenc...
As AI agents become increasingly capable of complex, long-horizon reasoning, rigorous and holistic evaluation is essential for measuring progress towa...