关键词 "medical expert" 的搜索结果， 共 20 条, 只显示前 480 条
A lightweight MCP server that enables AI assistants to search, retrieve, and analyze biomedical literature from PubMed.
A Model Context Protocol server providing AI assistants with access to healthcare data tools, including FDA drug information, PubMed research, health topics, clinical trials, and medical terminology l
Model Context Protocol Server for the Observational Medical Outcomes Partnership (OMOP) Common Data Model
MedixHub - A Model Context Protocol (MCP) server with a collection of medical and healthcare APIs and tools.
BioMCP: Biomedical Model Context Protocol
🔍 A biomedical literature annotation and relationship mining server based on PubTator3, providing convenient access through the MCP interface.
This project provides a modular Python wrapper for the LOINC API, with an MCP server interface that integrates seamlessly with Claude Desktop for intelligent medical terminology lookup and standardiza
Comprehensive notes for Graph Databases and MCP Servers in order to have enough context from a LM to quickly get up to speed on Graph DB projects.
A collection of Medical MCP servers.
A specialized MCP server for Claude Desktop that enhances AI-assisted medical learning
MCP server for medical calculations
A MCP Server for biomedical Literature Database
Sensei MCP is a Model Context Protocol (MCP) server that provides expert guidance for Dojo and Cairo development on Starknet.
A server for managing contextual data in DICOM tools, supporting medical imaging and machine learning workflows.
MCP server for searching and querying PubMed medical papers/research database
BAGEL是字节跳动开源的多模态基础模型，拥有140亿参数，其中70亿为活跃参数。采用混合变换器专家架构（MoT），通过两个独立编码器分别捕捉图像的像素级和语义级特征。BAGEL遵循“下一个标记组预测”范式进行训练，使用海量多模态标记数据进行预训练，包括语言、图像、视频和网络数据。在性能方面，BAGEL在多模态理解基准测试中超越了Qwen2.5-VL和InternVL-2.5等顶级开源视觉语言模型
Path is a team of more than 300+ image-editing experts and graphic designers who provide professional Photoshop services to e-commerce businesses, product photographers, and small and medium-sized bus
小红书hi lab（Humane Intelligence Lab，人文智能实验室）团队首次开源文本大模型 dots.llm1。 dots.llm1是一个中等规模的Mixture of Experts (MoE)文本大模型，在较小激活量下取得了不错的效果。该模型充分融合了团队在数据处理和模型训练效率方面的技术积累，并借鉴了社区关于 MoE 的最新开源成果。hi lab团队开源了所有模型和必要的训练
Lingshu是阿里巴巴达摩院推出的专注于医学领域的多模态大型语言模型。模型支持超过12种医学成像模态，包括X光、CT扫描、MRI等，在多模态问答、文本问答及医学报告生成等任务上展现出卓越的性能。Lingshu基于多阶段训练，逐步嵌入医学专业知识，显著提升在医学领域的推理和问题解决能力。推出7B、32B两个参数版本，其中32B版本在多个医学多模态问答任务中超越GPT-4.1等专有模型。Lingsh
MAI-DxO（Microsoft AI Diagnostic Orchestrator）是微软推出的先进人工智能系统，能提升医疗诊断的准确性和效率。基于模拟一组具有不同诊断方法的虚拟医生协作解决复杂的医疗案例。MAI-DxO能提出后续问题、订购检查，在获取新信息后更新推理，逐步缩小诊断范围。MAI-DxO能进行成本检查，确保在成本约束内做出诊断。在对《新英格兰医学杂志》发布的复杂病例进行测试时，
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