PubMed
PulseAugur coverage of PubMed — every cluster mentioning PubMed across labs, papers, and developer communities, ranked by signal.
- subsidiary of United States National Library of Medicine 100%
- subsidiary of National Center for Biotechnology Information 100%
- used by Gotit.pub 70%
- used by Influence Flower 70%
- used by CatalyzeX Code Finder for Papers 70%
- uses Gotit.pub 60%
- used by graph attention network 60%
- used by WikiCSSH: Extracting Computer Science Subject Headings from Wikipedia 60%
11 day(s) with sentiment data
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AI agent achieves 93.55% accuracy in genetic disease severity classification
Researchers have developed an AI agent that uses a combination of reasoning and retrieval-augmented generation to classify the severity of genetic diseases. This agent was trained on 10,211 Human Phenotype Ontology term…
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New system integrates medical case reports for rare disease diagnosis
Researchers have developed a multimodal information system that integrates structured clinical summaries from medical case reports, including images and biomedical entities. This system organizes information using a med…
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Video motion capture lacks clinical validation, review finds
A scoping review of 117 studies published between January 2015 and February 2026 found that video-based markerless motion capture is not yet a viable replacement for traditional marker-based systems in clinical settings…
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New CNN-BiLSTM framework offers factually grounded biomedical text summarization
Researchers have developed a new hybrid framework combining 1D-CNN and BiLSTM models for extractive summarization of biomedical and clinical texts. This approach aims to prevent factual inaccuracies common in abstractiv…
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New AI agent simplifies clinical trial data access using Gemini and DeepSeek
Researchers have developed ClinAgent, a conversational AI system designed to simplify the process of querying clinical trial registries. This system utilizes a ReAct-based Large Language Model (LLM) agent that integrate…
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AI and Deep Learning for Lung Cancer Detection: A Systematic Review
A systematic mapping study reviewed 96 articles from 2015 to the present on the application of artificial intelligence (AI) and deep learning (DL) for lung cancer detection in medical imaging. The research highlights th…
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Medical LLM research lags behind model releases, study finds
A recent study analyzing medical large language models from 2023 to 2026 reveals a widening gap between model release dates and the publication of research evaluating them. The research found that while the number of me…
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Trust in Scientists Linked to Shared Values, Not Expertise, Study Finds
A recent UK study indicates that public trust in scientists is primarily influenced by shared values and political identity, rather than their level of expertise. This finding aligns with observations of similar trends …
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Biomedical AI research faces reproducibility crisis from LLM retirement
A new study published on arXiv highlights a significant reproducibility risk in biomedical research due to the retirement of large language models (LLMs). Researchers found that 42% of papers using LLMs involved models …
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EPA proposal could end public comment on data center air pollution permits
The U.S. Environmental Protection Agency (EPA) has proposed a rule that would remove the federal requirement for states to notify the public and seek comment before issuing air pollution permits for data centers and oth…
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LLMs finetuned to automate process mining log generation from text
Researchers have developed a new framework using large-language models (LLMs) to automatically generate structured event logs from unstructured text. This method addresses the bottleneck of manually creating event logs,…
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OpenAI integrates ChatGPT Health with Epic EHR for clinician data access · 5 sources tracked
OpenAI has enhanced ChatGPT Health by integrating it with Epic's electronic health record (EHR) system, which serves over 325 million patients. This integration allows clinicians to securely import patient data, such as…
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New En-ViMedNER corpus aids Vietnamese biomedical NLP research
Researchers have introduced En-ViMedNER, the first parallel English-Vietnamese biomedical Named Entity Recognition (NER) corpus. This corpus is annotated with Unified Medical Language System (UMLS) semantic types, provi…
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New research questions usability of graph evidence in LLMs
A new research paper titled "Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs" explores the limitations of current graph-augmented large language models. The study introduces a diagnos…
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Hybrid search boosts biomedical research retrieval accuracy
A project explored hybrid search methods for biomedical research, combining dense and sparse vector retrieval to improve accuracy. The experiment focused on PubMed, a challenging dataset due to its mix of plain language…
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New Homo-RAG framework uses LLMs for cross-species gene function prediction
Researchers have developed Homo-RAG, a novel framework that uses large language models to predict gene function across different species. This system integrates homology-guided retrieval with evidence-aware ranking, lev…
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AI agent BioCheck Agent generates detailed biomedical fact-checking reports
Researchers have developed a new AI agent called BioCheck Agent, designed to generate detailed fact-checking reports for biomedical information. This agent utilizes an enhanced search strategy, exclusively querying PubM…
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89% of December PubMed papers show signs of AI-assisted writing
A recent study found that 89% of scientific papers published in December and archived on PubMed exhibited signs of AI-assisted writing. This indicates a significant and widespread adoption of AI tools in academic resear…
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New framework systematically compares strategies for aligning biomedical text and knowledge graphs
Researchers have developed a systematic framework for comparing lightweight strategies to align biomedical texts with knowledge graphs. This approach involves learning a projection between frozen text encoder and KG emb…
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Graph sparsification accelerates GNN pipelines, research finds
A new research paper explores graph sparsification as a method to accelerate Graph Neural Network (GNN) pipelines for large-scale graph machine learning. The study found that sparsification can preserve or even improve …