the Health Foundation
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Related Articles from SNS
Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models
Announce Type: new Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining useful life in engineered assets. These tasks are central to maintenance planning, but industrial PHM data are often fragmented, partially observed, and poorly labeled, which hinders supervised learning. Foundation models offer a route toward reusable predictive systems, yet most time-series foundation models are...
A Foundation Model for Wearable Movement Data in Mental Health Research
arXiv:2411.15240v5 Announce Type: replace Abstract: Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, reflecting fine-grained temporal behavioral trends. Despite its promise, the development of foundation models for health wearable modeling remains limited when compared to clinical image and text analysis. We designed transformers with patch embeddings and used self-supervised masked autoencoder...
Fraudster nurse struck off from NHS after claiming £19k in fake shifts
Fraudster nurse struck off from NHS after claiming £19k in fake shifts Former nurse Faith Chareka added dozens of shifts she did not work to her rota, claiming almost £20,000 from Frimley Health NHS Foundation Trust in Surrey A nurse has been struck off for fraudulently claiming almost £20,000 for shifts she never worked. Faith Chareka, who worked in the emergency department for Frimley Health NHS Foundation Trust in Surrey, was convicted of fraud by abuse of position after adding 50 shifts...
Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints
Announce Type: replace Abstract: Clinical prediction from structured electronic health records (EHRs) is challenging due to high dimensionality, heterogeneity, class imbalance, and distribution shift. While tabular in-context learning (TICL) and retrieval-augmented methods perform well on generic benchmarks, their behavior in clinical settings remains unclear. We present a multi-cohort EHR benchmark comparing classical, deep tabular, and TICL models across varying data scale, feature...
Armed with AI, study identifies prey from predator crunching sounds
Armed with AI, study identifies prey from predator crunching sounds Lisa Lock Scientific Editor Robert Egan Associate Editor Interactions between hard-shelled marine mollusks such as clams and snails and their predators play a critical but largely unseen role in shaping coastal ecosystems. These organisms help stabilize shorelines, filter water and support biodiversity, making them foundational to coastal health. Yet they are increasingly threatened by ocean acidification and expanding...
ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning
arXiv:2606.02802v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model structured longitudinal electronic health records (EHRs). In contrast, EHR foundation models can learn predictive patient representations, yet lack interpretable language-based reasoning. To bridge this gap, we propose ChatHealthAI, a multimodal reasoning framework that aligns structured EHR...
ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning
arXiv:2606.02802v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model structured longitudinal electronic health records (EHRs). In contrast, EHR foundation models can learn predictive patient representations, yet lack interpretable language-based reasoning. To bridge this gap, we propose ChatHealthAI, a multimodal reasoning framework that aligns structured EHR...
Bayesian Spectral Emotion Transition Discovery from Multi-Annotator Disagreement
arXiv:2606.01906v1 Announce Type: new Abstract: Emotions evolve through the dynamics of conversation, and understanding their transition structure is foundational to applications ranging from mental-health screening to dialogue systems. However, existing studies typically compress multi-rater judgments into a single hard label by majority voting, discarding the uncertainty signal needed to understand turn-to-turn transitions. In this article, we propose Bayesian Spectral Emotion Transition...
SAM for Robust Mitochondria Instance Segmentation in Fluorescence Microscopy
Announce Type: new Abstract: The morphological analysis of mitochondria in fluorescence microscopy (FM) is crucial for understanding cellular health, energy production, and metabolic regulation. While foundation models like the Segment Anything Model (SAM) have revolutionized natural image segmentation, their direct application to FM is hindered by a significant domain shift characterized by diffraction-limited resolution, low contrast, and complex overlapping organelle networks....
Childcare problems are compounded for dual doctor couples
McNally correctly identifies that many of the challenges affecting parents who are doctors are compounded for trainees with frequent rotations and often long commutes.1 Being a dual doctor couple, which has become increasingly common, further compounds the problem. The degree of influence that trainees have over their rotations varies considerably across grade, region, and training programme. We started a family during higher specialty training, but there are many parents in foundation or...