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

3 citations · 7 across the 8 of their papers we have counts for

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cs.CL2024★ 1 cited

Evaluating Large Language Models for Health-Related Text Classification Tasks with Public Social Media Data

Yuting Guo, Anthony Ovadje, Mohammed Ali Al-Garadi +1

Large language models (LLMs) have demonstrated remarkable success in NLP tasks. However, there is a paucity of studies that attempt to evaluate their performances on social media-b…

cs.CL2024★ 2 cited

Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing

Seibi Kobara, Alireza Rafiei, Masoud Nateghi +3

Breast cancer is a significant public health concern and is the leading cause of cancer-related deaths among women. Despite advances in breast cancer treatments, medication non-adh…

cs.CL2024★ 3 cited

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

Yuting Guo, Seyedeh Somayyeh Mousavi, Reza Sameni +1

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 ind…

q-bio.QM2024★ 1 cited

Learning from Two Decades of Blood Pressure Data: Demography-Specific Patterns Across 75 Million Patient Encounters

Seyedeh Somayyeh Mousavi, Yuting Guo, Abeed Sarker +1

Hypertension is a global health concern with an increasing prevalence, underscoring the need for effective monitoring and analysis of blood pressure (BP) dynamics. We analyzed a su…