关键词 "medical scribing" 的搜索结果， 共 19 条, 只显示前 480 条
Create professional digital rubber stamps with StampJam, ideal for digital and physical documents.
Real-time speech-to-text and text-to-speech APIs powered by Deepgram's voice AI models
医学成像分割比赛，用于通用算法的验证和测试，涵盖广泛的挑战，例如：小数据、不平衡标签、大范围对象尺度、多类别标签和多模态成像等。本次挑战赛和数据集旨在通过开源多个高度不同任务的大型医学成像数据集，并标准化分析和验证流程，提供此类资源。
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
MCP Server for transcribing videos via video links and summarizing video content
🔍 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
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
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
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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