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LLM4CKD: Large Language Models for Early Stage Chronic Kidney Disease Screening

Paper recorded by Signals 4 on 2026-09-03 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-03 on arXiv · recorded by Signals 4 on 2026-09-04

Category: cs.LG · 机器学习 · first seen 2026-09-04

Abstract

Early screening of chronic kidney disease (CKD) is critical for timely intervention, yet most machine learning (ML) and deep learning (DL) approaches require labeled data and model training, limiting their use in real-world screening settings. This study evaluates the effectiveness of large language models (LLMs) for CKD screening under zero-shot and few-shot in-context learning settings and compa

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#140 most recent of 215 cs.LG papers we have recorded · ↑ newer: A location-invariant estimator of extremal quantile treatment effects · ↓ older: Differentiable Hybrid Modelling for Learning and Optimising Chemical T
Cite this page: LLM4CKD: Large Language Models for Early Stage Chronic Kidney Disease Screening: the #140 most recent of 215 cs.LG papers we have recorded (as of 2026-09-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/llm4ckd-large-language-models-for-early-stage-chronic-kidney-disease-screening.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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