electronic health records
PulseAugur coverage of electronic health records — every cluster mentioning electronic health records across labs, papers, and developer communities, ranked by signal.
- used by intensive care unit 90%
- instance of ScienceCast 70%
- used by alphaXiv 70%
- used by MIMIC-III, a freely accessible critical care database 70%
- used by ScienceCast 70%
- used by Gotit.pub 70%
- used by CatalyzeX 60%
- used by scite Smart Citations 60%
- instance of Connected Papers 60%
- used by Litmaps 60%
- other Gotit.pub 50%
- instance of intensive care unit 50%
- 2026-09-15 regulatory The Trump EPA is moving to eliminate remaining greenhouse-gas rules for power plants, asserting that emissions have no material impact on climate change. source
- 2026-09-14 regulatory The EPA is expected to announce the elimination of limits on climate pollution from power plants. source
- 2026-08-27 regulatory The EPA is being sued for allegedly fast-tracking the approval of toxic chemicals used in semiconductor manufacturing. source
- 2026-05-27 regulatory The EPA proposed new rules to expedite data center construction by modifying air permitting processes. source
- 2026-05-22 regulatory The EPA has promised an investigation into allegations that a Meta data center construction project has contaminated the drinking water supply in Morgan County, Georgia. source
- 2026-05-22 regulatory The EPA has promised to investigate allegations of water pollution linked to a Meta data center construction project in Morgan County, Georgia. source
9 day(s) with sentiment data
-
AI models need up to 18 years of EHR data for colorectal cancer prediction
Researchers have introduced the concept of "time-context" to evaluate how far back in time an AI model needs to look for predictive signals in electronic health records (EHRs). A study using a transformer model on EHR d…
-
Trustworthy AI hinges on data context, permissions, and clear rules
Building trustworthy AI requires a robust data foundation that goes beyond simply consolidating information. Companies must establish clear rules for data definition, ownership, and transformation to ensure consistency …
-
DocTalk system enhances medical LLM retrieval with chain-of-thought reasoning
Researchers have developed DocTalk, a question-answering system designed to improve medical knowledge retrieval from electronic health records. The system utilizes fine-tuned large language models with chain-of-thought …
-
US Govt claims power to dismiss environmental lawsuits, targets Musk's data center
The U.S. government has asserted its authority to dismiss any citizen's lawsuit aimed at enforcing federal environmental laws, potentially overriding Congress's explicit intentions. This stance was highlighted in a fili…
-
New adapter EHRAdapt integrates EHR data with language models
Researchers have developed EHRAdapt, a novel adapter designed to integrate electronic health records (EHRs) with pretrained language models. This adapter maps EHR data directly into the model's embedding space, addressi…
-
Smart TV tracking bypasses opt-outs; Trump EPA pollution lawsuit claim rejected
Research indicates that opting out of smart TV tracking may not be effective, as suspicious traffic patterns were observed. The author of the research suggests that operating system providers are unlikely to discard thi…
-
AI framework visualizes cancer care team dynamics and patient risk
Researchers have developed a visual analytics framework to model and interpret the evolving dynamics of care teams in cancer treatment. By analyzing communication data from electronic health records, they use a temporal…
-
Dissertation advances offline Apprenticeship Learning for human-centric AI
This dissertation introduces novel frameworks for offline Apprenticeship Learning (AL) designed for human-centric environments like Intelligent Tutoring Systems (ITSs) and clinical healthcare. The proposed methods, incl…
-
AI research papers explore crystal generation and EHR modeling
Two new research papers have been published on arXiv, detailing advancements in distinct AI applications. The first, titled "CrystalAR: Autoregressive Modeling for Symmetric Crystal Generation," introduces a novel frame…
-
New framework improves oncology record retrieval by allocating evidence over time
Researchers have developed a new framework called OncoCONSTRUE to improve the retrieval of information from electronic health records in oncology. The system addresses the issue of temporal redundancy, where repeated in…
-
New GraphBEAT Framework Enhances Cancer Risk Stratification from EHRs
Researchers have developed GraphBEAT, a novel temporal graph representation learning framework designed to improve early risk stratification for gastrointestinal cancers using electronic health records (EHRs). This meth…
-
New framework boosts LLM accuracy for emergency care prediction
Researchers have developed TIR-EC, a novel framework that enhances large language models (LLMs) for predicting post-arrival emergency care needs. This system addresses LLM limitations in feature selection and numerical …
-
German health research center to use AI and ePA data
The German Federal Institute for Health Research (FDZ-Gesundheit) plans to leverage artificial intelligence and electronic health record (ePA) data to become a major research hub. This initiative aims to enhance data ac…
-
New ProCARE framework automates real-world healthcare studies using LLM agents
Researchers have developed ProCARE, a framework designed to automate real-world studies (RWS) using large language model agents. ProCARE addresses the brittleness of current RWS automation by converting heterogeneous da…
-
New MedHarnessBench evaluates healthcare AI agents on process quality
Researchers have introduced MedHarnessBench, a new benchmark designed to evaluate healthcare agents. This benchmark focuses on seven critical process dimensions beyond just task completion, including care action fulfill…
-
McKinsey identifies major untapped potential in electronic health records
McKinsey & Company has identified electronic health records (EHRs) as a significant area with untapped potential. The firm's analysis suggests that optimizing the use and integration of EHRs could lead to substantial be…
-
New LLM framework PaReGTA enhances patient representation from EHR data
Researchers have developed PaReGTA, a novel framework that leverages Large Language Models (LLMs) to create patient representations from electronic health records (EHRs). This method converts longitudinal EHR data into …
-
New contrastive learning method improves cross-national EHR data transfer
Researchers have developed a new pre-training objective called Asymmetric Supervised Contrastive Learning (Asymmetric SupCon) to improve the transferability of Electronic Health Record (EHR) representations across diffe…
-
Retired MD criticizes EHRs and AI notes for worsening physician documentation burden
A retired Primary Care MD discusses the long-standing issue of excessive documentation time for physicians, exacerbated by the widespread adoption of Electronic Medical Records (EMRs) and Electronic Health Records (EHRs…
-
DeepAJM: New Deep Learning Model Enhances Survival Outcome Prediction
Researchers have developed DeepAJM, a novel deep learning joint model designed to predict survival outcomes by analyzing longitudinal data trajectories. Unlike traditional parametric models that rely on fixed assumption…