arXiv AI August 17, 2026 By Yuting Guo, Seyedeh Somayyeh Mousavi, Reza Sameni, Abeed Sarker

Leveraging Few-Shot Learning and Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature

arXiv:2402. 01826v2 Announce Type: replace-cross Abstract: Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for individual demographic factors such as sex and age.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 24

LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes

arXiv:2603. 13673v2 Announce Type: replace Abstract: Accurate extraction of Alzheimer's Disease and Related Dementias (ADRD) phenotypes from electronic health records (EHR) is critical for early-stage detection and disease staging.

By Mingchen Shao, Yuzhang Xie, Carl Yang, Jiaying Lu

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arXiv AI

Jun 2

LLMs for Cardiovascular Risk Prediction from Structured Clinical Data

arXiv:2606. 00031v1 Announce Type: cross Abstract: Coronary artery disease (CAD) remains one of the leading causes of death globally, highlighting the need for reliable predictive systems to support early diagnosis and risk assessment.

By Jeba Maliha, Md Rafiul Kabir

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arXiv AI

Jun 16

Few-Shot Biomedical Relation Extraction with Large Language Models: A Viable Alternative to Supervised Learning?

arXiv:2606. 15412v1 Announce Type: cross Abstract: Biomedical relation extraction (BioRE) is a key step in transforming biomedical literature into structured knowledge.

By Jakob Mraz, Toma\v{z} Curk, Bla\v{z} Zupan

llms

arXiv AI

Jun 9

Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learning

arXiv:2606. 08311v1 Announce Type: new Abstract: Electronic health record (EHR) notes are dense medical documents containing large amounts of information, often filled with complex medical jargon.

By Mahshad Koohi Habibi Dehkordi, Shuxin Zhou, Yehoshua Perl, Fadi P. Deek, James Geller, Gai Elhanan, Andrew J. Einstein, Luke Lindemann, Vipina K. Keloth

arXiv AI

Jun 12

EDEN: A Large-Scale Corpus of Clinical Notes for Italian

arXiv:2606. 12569v1 Announce Type: cross Abstract: We present EDEN (Emergency Department Electronic Notes), a new and unique large-scale corpus of clinical notes produced in Emergency Departments of Italian hospitals.

By Tiziano Labruna, Guido Bertolini, Pietro Ferrazzi, Bernardo Magnini

llms benchmarks

arXiv AI

Jun 19

Ensembles of Large Language Models for Identifying EQ-5D Studies in PubMed Based on Their Abstracts

arXiv:2606. 19345v1 Announce Type: cross Abstract: The rapid increase in scientific publications leads to the fact that manual study screening in systematic literature reviews (SLRs) is increasingly resource consuming, inefficient, and inconsistent.

By Zhyar Rzgar K. Rostam, M\'arta P\'entek, J\'anos Tibor Czere, Zsombor Zrubka, L\'aszl\'o Gul\'acsi, G\'abor Kert\'esz

llms safety

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LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes

LLMs for Cardiovascular Risk Prediction from Structured Clinical Data

Few-Shot Biomedical Relation Extraction with Large Language Models: A Viable Alternative to Supervised Learning?

Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learning

EDEN: A Large-Scale Corpus of Clinical Notes for Italian

Ensembles of Large Language Models for Identifying EQ-5D Studies in PubMed Based on Their Abstracts