学术写作

325 Ahmad-Fathinejad/Title-Abstract-Screening SLM-PICO-Screener 是用于自动化系统综述筛选的轻量 NLP 流水线，基于 Phi-3 Mini 配合 LoRA 与 4-bit 量化，将文章分类为 8 个 PICO 标签。体积约 90 MB，可在消费级 GPU/CPU 上运行，加速生物医学研究中的证据综合。SLM-PICO-Screener is a lightweight NLP pipeline automating systematic review screening. Built on Phi-3 Mini with LoRA & 4-bit quantization, it classifies articles into 8 PICO labels. At ~90 MB, it runs on consumer GPUs/CPU, accelerating evidence synthesis in biomedical research. 证据综述 文献筛选与信息抽取 系统综述Meta 分析与证据综合 引用 LLM 基础设施 Jupyter Notebook 0 ★ 326 aget-framework/template-reviewer-aget 系统综述与验证的质量模板——扩展 Consultant 角色原型。Quality template for systematic review and validation - Extends Consultant archetype 证据综述 系统综述 引用模板 Agent 智能体 Python 0 ★ 327 adrianstier/regen-2026-coral-regeneration-meta 珊瑚损伤后再生：PRISMA 系统综述与 meta 分析Coral regeneration after wounding: PRISMA systematic review and meta-analysis 证据综述 系统综述 Meta 分析与证据综合 引用 工程化 HTML 0 ★ 328 adrianstier/coral-regeneration-meta-analysis 珊瑚损伤后再生的 PRISMA 系统综述与 meta 分析。Coral regeneration after wounding: PRISMA systematic review and meta-analysis 证据综述 Meta 分析与证据综合 系统综述 引用 工程化 HTML 0 ★ 329 adnan-mayof/PRISMA-Guided-Systematic-Review-and-Meta-Analysis-Workflow 证据综述 系统综述 Meta 分析与证据综合 引用 工程化 0 ★ 330 Aditya2623/OncoRAG OncoRAG 是一个 RAG 系统，为临床医生和研究人员提供即时获取最新肿瘤学证据的能力——来源包括直接来自 PubMed 的随机对照试验、Meta 分析、系统综述和 III 期临床试验。提出临床问题，即可获得带引文的可靠答案。OncoRAG is a Retrieval-Augmented Generation system that gives clinicians and researchers instant access to the latest oncology evidence — drawing from Randomized Controlled Trials, Meta-Analyses, Systematic Reviews, and Phase III Clinical Trials sourced directly from PubMed. Ask a clinical question, get a grounded answer with citations. 证据综述 系统综述 引用 RAG 检索增强 Python 0 ★ 331 ADBarshan/diagnostic-accuracy-of-AI-VS-RAdiologist-in-Breast-Carcinoma-Detection-via-Mammography 人工智能（AI）已成为提升乳腺 X 线摄影对乳腺癌诊断准确性的潜力工具。本系统综述与荟萃分析旨在探讨 AI 与放射科医生通过乳腺 X 线摄影检测乳腺癌的准确性。Artificial intelligence (AI) has emerged as a promising tool to improve the diagnostic accuracy of 49 mammography for breast carcinoma detection. This systematic review and meta-analysis aim to 50 explore the accuracy of AI and radiologists in breast carcinoma detection via mammography 证据综述 Meta 分析与证据综合 系统综述 引用 评测基准 0 ★ 332 0Nguyen0Cong0Tuan0/thesis-all Spec-FastGS 论文工作区：代码、已下载论文库 + 文献综述、分析与报告。Spec-FastGS thesis workspace: code, downloaded paper library + literature review, analysis, and report. 证据综述 系统综述 写作 工程化 Jupyter Notebook 0 ★