{"id":36567,"date":"2025-01-14T03:00:39","date_gmt":"2025-01-13T19:00:39","guid":{"rendered":"https:\/\/17aitech.com\/?p=36567"},"modified":"2025-01-14T03:00:39","modified_gmt":"2025-01-13T19:00:39","slug":"%e8%b0%b7%e6%ad%8c%e3%80%81mit%e7%ad%89%e5%bc%80%e5%8f%91%e5%a4%9a%e6%99%ba%e8%83%bd%e4%bd%93%e5%8c%bb%e7%96%97%e5%86%b3%e7%ad%96%e6%a1%86%e6%9e%b6mdagents%ef%bc%8c%e5%8c%bb%e5%ad%a6llm%e6%96%b0","status":"publish","type":"post","link":"https:\/\/17aitech.com\/?p=36567","title":{"rendered":"\u8c37\u6b4c\u3001MIT\u7b49\u5f00\u53d1\u591a\u667a\u80fd\u4f53\u533b\u7597\u51b3\u7b56\u6846\u67b6MDAgents\uff0c\u533b\u5b66LLM\u65b0\u7528\u6cd5"},"content":{"rendered":"

\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:\u8c37\u6b4c\u3001MIT\u7b49\u5f00\u53d1\u591a\u667a\u80fd\u4f53\u533b\u7597\u51b3\u7b56\u6846\u67b6MDAgents\uff0c\u533b\u5b66LLM\u65b0\u7528\u6cd5<\/a><\/p>\n

<\/a><\/p>\n

\u7f16\u8f91 | \u767d\u83dc\u53f6<\/p>\n

\u57fa\u7840\u6a21\u578b\u6b63\u5728\u6210\u4e3a\u533b\u5b66\u9886\u57df\u7684\u5b9d\u8d35\u5de5\u5177\u3002\u7136\u800c\uff0c\u5c3d\u7ba1\u5b83\u4eec\u524d\u666f\u5e7f\u9614\uff0c\u4f46\u5728\u590d\u6742\u7684\u533b\u5b66\u4efb\u52a1\u4e2d\u5982\u4f55\u6700\u597d\u5730\u5229\u7528\u5927\u578b\u8bed\u8a00\u6a21\u578b<\/mark> (LLM) \u4ecd\u662f\u4e00\u4e2a\u60ac\u800c\u672a\u51b3\u7684\u95ee\u9898\u3002<\/p>\n

\u9ebb\u7701\u7406\u5de5\u5b66\u9662\u3001\u8c37\u6b4c\u7814\u7a76\u9662\u548c\u9996\u5c14\u56fd\u7acb\u5927\u5b66\u533b\u9662\u7684\u7814\u7a76\u4eba\u5458\u63d0\u51fa\u4e86\u4e00\u79cd\u65b0\u9896\u7684\u591a\u667a\u80fd\u4f53\u6846\u67b6\uff0c\u79f0\u4e3a\u533b\u7597\u51b3\u7b56\u667a\u80fd\u4f53 (MDAgents)\uff0c\u5b83\u901a\u8fc7\u81ea\u52a8\u4e3a LLM \u56e2\u961f\u5206\u914d\u534f\u4f5c\u7ed3\u6784\u6765\u5e2e\u52a9\u89e3\u51b3\u8fd9\u4e00\u5dee\u8ddd\u3002<\/p>\n

\u6307\u5b9a\u7684\u4e2a\u4eba\u6216\u5c0f\u7ec4\u534f\u4f5c\u7ed3\u6784\u662f\u6839\u636e\u624b\u5934\u7684\u533b\u7597\u4efb\u52a1\u91cf\u8eab\u5b9a\u5236\u7684\uff0c\u6a21\u62df\u9002\u5e94\u4e0d\u540c\u590d\u6742\u7a0b\u5ea6\u4efb\u52a1\u7684\u771f\u5b9e\u533b\u7597\u51b3\u7b56\u8fc7\u7a0b\u3002\u8be5\u56e2\u961f\u4f7f\u7528\u6700\u5148\u8fdb\u7684 LLM \u5728\u4e00\u7cfb\u5217\u771f\u5b9e\u533b\u5b66\u77e5\u8bc6\u548c\u533b\u5b66\u8bca\u65ad\u57fa\u51c6<\/mark>\u4e2d\u8bc4\u4f30\u4ed6\u4eec\u7684\u6846\u67b6\u548c\u57fa\u7ebf\u65b9\u6cd5\uff0c\u5305\u62ec\u5c06 LLM \u7684\u533b\u7597\u590d\u6742\u6027\u5206\u7c7b\u4e0e\u4eba\u7c7b\u533b\u751f\u8fdb\u884c\u6bd4\u8f83\u3002<\/p>\n

\u5728\u9700\u8981\u7406\u89e3\u533b\u5b66\u77e5\u8bc6\u548c\u591a\u6a21\u6001\u63a8\u7406\u7684\u4efb\u52a1\u4e2d\uff0cMDAgents \u5728\u5341\u9879\u57fa\u51c6<\/mark>\u6d4b\u8bd5\u4e2d\u7684\u4e03\u9879\u4e2d\u53d6\u5f97\u4e86\u6700\u4f73\u8868\u73b0\uff0c\u4e0e\u4ee5\u524d\u65b9\u6cd5\u7684\u6700\u4f73\u8868\u73b0\u76f8\u6bd4\uff0c\u5176\u663e\u8457\u63d0\u9ad8\u4e86 4.2% (p < 0.05)\u3002<\/p>\n

\u6d88\u878d\u7814\u7a76\u8868\u660e\uff0cMDAgents \u53ef\u4ee5\u6709\u6548\u786e\u5b9a\u533b\u5b66\u590d\u6742\u6027\uff0c\u4ece\u800c\u4f18\u5316\u5404\u79cd\u533b\u5b66\u4efb\u52a1\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u5728\u5c0f\u7ec4\u534f\u4f5c\u4e2d\uff0c\u4e3b\u6301\u4eba\u8bc4\u5ba1\u548c\u5916\u90e8\u533b\u5b66\u77e5\u8bc6\u7684\u7ed3\u5408\u4f7f\u5e73\u5747\u51c6\u786e\u5ea6\u63d0\u9ad8\u4e86 11.8%\u3002<\/p>\n

\u8be5\u7814\u7a76\u4ee5\u300cMDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making<\/em>\u300d\u4e3a\u9898\uff0c\u4e8e 2024 \u5e74 10 \u6708 30 \u65e5\u66f4\u65b0\u5728 arXiv<\/em> \u9884\u5370\u5e73\u53f0\u3002<\/p>\n

<\/a><\/p>\n

\u57fa\u7840\u6a21\u578b\u5728\u533b\u5b66\u9886\u57df\u524d\u666f\u5e7f\u9614\uff0c\u5c24\u5176\u662f\u5728\u534f\u52a9\u5b8c\u6210\u533b\u7597\u51b3\u7b56 (MDM) \u7b49\u590d\u6742\u4efb\u52a1\u65b9\u9762\u3002MDM \u662f\u4e00\u4e2a\u7ec6\u81f4\u5165\u5fae\u7684\u8fc7\u7a0b\uff0c\u8981\u6c42\u4e34\u5e8a\u533b\u751f\u5206\u6790\u5404\u79cd\u6570\u636e\u6e90\uff08\u5982\u5f71\u50cf\u3001\u7535\u5b50\u5065\u5eb7\u8bb0\u5f55\u548c\u9057\u4f20\u4fe1\u606f\uff09\uff0c\u540c\u65f6\u9002\u5e94\u65b0\u7684\u533b\u5b66\u7814\u7a76\u3002<\/p>\n

LLM \u53ef\u4ee5\u901a\u8fc7\u7efc\u5408\u4e34\u5e8a\u6570\u636e\u5e76\u5b9e\u73b0\u6982\u7387\u548c\u56e0\u679c\u63a8\u7406\u6765\u652f\u6301 MDM\u3002\u7136\u800c\uff0c\u7531\u4e8e\u9700\u8981\u9002\u5e94\u6027\u5f3a\u7684\u591a\u5c42\u65b9\u6cd5\uff0c\u5c06 LLM \u5e94\u7528\u4e8e\u533b\u7597\u4fdd\u5065\u9886\u57df\u4ecd\u7136\u5177\u6709\u6311\u6218\u6027\u3002\u5c3d\u7ba1\u591a\u667a\u80fd\u4f53 LLM \u5728\u5176\u4ed6\u9886\u57df\u663e\u793a\u51fa\u6f5c\u529b\uff0c\u4f46\u5b83\u4eec\u76ee\u524d\u7684\u8bbe\u8ba1\u7f3a\u4e4f\u4e0e\u6709\u6548\u4e34\u5e8a\u5e94\u7528\u6240\u5fc5\u9700\u7684\u534f\u4f5c\u5f0f\u3001\u5206\u5c42\u51b3\u7b56\u7684\u96c6\u6210\u3002<\/p>\n

LLM \u8d8a\u6765\u8d8a\u591a\u5730\u5e94\u7528\u4e8e\u533b\u5b66\u4efb\u52a1\uff0c\u4f8b\u5982\u56de\u7b54\u533b\u5b66\u8003\u8bd5\u95ee\u9898\u3001\u9884\u6d4b\u4e34\u5e8a\u98ce\u9669\u3001\u8bca\u65ad\u3001\u751f\u6210\u62a5\u544a\u548c\u521b\u5efa\u7cbe\u795e\u75c5\u8bc4\u4f30\u3002\u533b\u5b66 LLM \u7684\u6539\u8fdb\u4e3b\u8981\u6e90\u4e8e\u4f7f\u7528\u4e13\u95e8\u6570\u636e\u8fdb\u884c\u8bad\u7ec3\u6216\u4f7f\u7528\u63a8\u7406\u65f6\u95f4\u65b9\u6cd5\uff0c\u4f8b\u5982\u5373\u65f6\u5de5\u7a0b\u548c\u68c0\u7d22\u589e\u5f3a\u751f\u6210 (RAG)\u3002<\/p>\n

\u901a\u7528\u6a21\u578b\uff08\u5982 GPT-4\uff09\u901a\u8fc7\u9ad8\u7ea7\u63d0\u793a\u5728\u533b\u5b66\u57fa\u51c6<\/mark>\u4e0a\u8868\u73b0\u826f\u597d\u3002\u591a\u667a\u80fd\u4f53\u6846\u67b6\u63d0\u9ad8\u4e86\u51c6\u786e\u6027\uff0c\u667a\u80fd\u4f53\u901a\u8fc7\u534f\u4f5c\u6216\u8fa9\u8bba\u6765\u89e3\u51b3\u590d\u6742\u4efb\u52a1\u3002\u7136\u800c\uff0c\u73b0\u6709\u7684\u9759\u6001\u6846\u67b6\u53ef\u80fd\u4f1a\u9650\u5236\u4e0d\u540c\u4efb\u52a1\u7684\u6027\u80fd\uff0c\u56e0\u6b64\u52a8\u6001\u591a\u667a\u80fd\u4f53\u65b9\u6cd5\u53ef\u80fd\u66f4\u597d\u5730\u652f\u6301\u590d\u6742\u7684\u533b\u7597\u51b3\u7b56\u3002<\/p>\n

\u9ebb\u7701\u7406\u5de5\u5b66\u9662\u3001\u8c37\u6b4c\u7814\u7a76\u9662\u548c\u9996\u5c14\u56fd\u7acb\u5927\u5b66\u533b\u9662\u5f00\u53d1\u4e86 MDAgents\uff0c\u8fd9\u662f\u4e00\u4e2a\u591a\u667a\u80fd\u4f53\u6846\u67b6\uff0c\u65e8\u5728\u6839\u636e\u533b\u7597\u4efb\u52a1\u7684\u590d\u6742\u6027\u52a8\u6001\u5206\u914d LLM \u4e4b\u95f4\u7684\u534f\u4f5c\uff0c\u6a21\u62df\u73b0\u5b9e\u4e16\u754c\u7684\u533b\u7597\u51b3\u7b56\u3002<\/p>\n

<\/a><\/p>\n

\u56fe\u793a\uff1aMDAgents \u6846\u67b6\u3002\uff08\u6765\u6e90\uff1a\u8bba\u6587\uff09<\/section>\n

MDAgents \u53ef\u4ee5\u6839\u636e\u5177\u4f53\u4efb\u52a1\u81ea\u9002\u5e94\u5730\u9009\u62e9\u5355\u72ec\u6216\u56e2\u961f\u534f\u4f5c\uff0c\u5728\u5404\u79cd\u533b\u7597\u57fa\u51c6<\/mark>\u6d4b\u8bd5\u4e2d\u8868\u73b0\u826f\u597d\u3002\u5b83\u5728 10 \u4e2a\u57fa\u51c6<\/mark>\u6d4b\u8bd5\u4e2d\u7684 7 \u4e2a\u4e2d\u8d85\u8d8a\u4e86\u4e4b\u524d\u7684\u65b9\u6cd5\uff0c\u51c6\u786e\u7387<\/mark>\u63d0\u9ad8\u4e86 4.2%\u3002\u5173\u952e\u6b65\u9aa4\u5305\u62ec\u8bc4\u4f30\u4efb\u52a1\u590d\u6742\u6027\u3001\u9009\u62e9\u5408\u9002\u7684\u667a\u80fd\u4f53\u548c\u7efc\u5408\u54cd\u5e94\uff0c\u901a\u8fc7\u5c0f\u7ec4\u8bc4\u5ba1\u53ef\u5c06\u51c6\u786e\u7387<\/mark>\u63d0\u9ad8 11.8%\u3002MDAgents \u8fd8\u901a\u8fc7\u8c03\u6574\u667a\u80fd\u4f53\u4f7f\u7528\u6765\u5e73\u8861\u6027\u80fd\u548c\u6548\u7387\u3002<\/p>\n

MDAgents \u6846\u67b6\u56f4\u7ed5\u533b\u7597\u51b3\u7b56\u7684\u56db\u4e2a\u5173\u952e\u9636\u6bb5\u6784\u5efa\uff1a<\/p>\n

\u9996\u5148\u8bc4\u4f30\u533b\u7597\u67e5\u8be2\u7684\u590d\u6742\u7a0b\u5ea6\uff0c\u5c06\u5176\u5206\u4e3a\u4f4e\u3001\u4e2d\u3001\u9ad8\uff1b<\/p>\n

\u6839\u636e\u6b64\u8bc4\u4f30\uff0c\u62db\u52df\u5408\u9002\u7684\u4e13\u5bb6\uff1a\u9488\u5bf9\u8f83\u7b80\u5355\u7684\u75c5\u4f8b\uff0c\u62db\u52df\u5355\u4e2a\u4e34\u5e8a\u533b\u751f\uff1b\u9488\u5bf9\u8f83\u590d\u6742\u7684\u75c5\u4f8b\uff0c\u62db\u52df\u591a\u5b66\u79d1\u56e2\u961f\uff1b<\/p>\n

\u7136\u540e\uff0c\u5206\u6790\u9636\u6bb5\u5c06\u6839\u636e\u6848\u4f8b\u7684\u590d\u6742\u7a0b\u5ea6\u91c7\u7528\u4e0d\u540c\u7684\u65b9\u6cd5\uff0c\u5305\u62ec\u4ece\u4e2a\u4eba\u8bc4\u4f30\u5230\u534f\u4f5c\u8ba8\u8bba\uff1b<\/p>\n

\u6700\u540e\uff0c\u7cfb\u7edf\u7efc\u5408\u6240\u6709\u89c1\u89e3\u4ee5\u5f62\u6210\u7ed3\u8bba\u6027\u51b3\u7b56\uff0c\u51c6\u786e\u7684\u7ed3\u679c\u8868\u660e\uff0c\u4e0e\u5355\u667a\u80fd\u4f53\u548c\u5176\u4ed6\u591a\u667a\u80fd\u4f53\u8bbe\u7f6e\u76f8\u6bd4\uff0cMDAgents \u5728\u5404\u79cd\u533b\u7597\u57fa\u51c6<\/mark>\u4e0a\u90fd\u5177\u6709\u6709\u6548\u6027\u3002<\/p>\n

<\/a><\/p>\n

\u56fe\u793a\uff1aPMC-VQA \u6570\u636e\u96c6\u4e2d\u4e2d\u7b49\u590d\u6742\u7a0b\u5ea6\u6848\u4f8b\u4e2d MDAgents \u7684\u8bf4\u660e\u6027\u793a\u4f8b\u3002\uff08\u6765\u6e90\uff1a\u8bba\u6587\uff09<\/p>\n

\u8be5\u7814\u7a76\u5728 Solo\u3001Group \u548c Adaptive \u6761\u4ef6\u4e0b\u8bc4\u4f30\u4e86\u5404\u79cd\u533b\u7597\u57fa\u51c6<\/mark>\u6d4b\u8bd5\u4e2d\u7684\u6846\u67b6\u548c\u57fa\u7ebf\u6a21\u578b\uff0c\u663e\u793a\u51fa\u663e\u8457\u7684\u7a33\u5065\u6027\u548c\u6548\u7387\u3002<\/p>\n

Adaptive \u65b9\u6cd5 MDAgents \u53ef\u6839\u636e\u4efb\u52a1\u590d\u6742\u6027\u6709\u6548\u8c03\u6574\u63a8\u7406\uff0c\u5e76\u5728\u5341\u4e2a\u57fa\u51c6<\/mark>\u6d4b\u8bd5\u4e2d\u7684\u4e03\u4e2a\u4e2d\u59cb\u7ec8\u4f18\u4e8e\u5176\u4ed6\u8bbe\u7f6e\u3002<\/p>\n

\u6d4b\u8bd5\u00a0MedQA\u00a0\u548c Path-VQA \u7b49\u6570\u636e\u96c6\u7684\u7814\u7a76\u4eba\u5458\u53d1\u73b0\uff0c\u81ea\u9002\u5e94\u590d\u6742\u5ea6\u9009\u62e9\u53ef\u63d0\u9ad8\u51b3\u7b56\u51c6\u786e\u6027\u3002<\/p>\n

<\/a><\/p>\n

\u56fe\u793a\uff1a\u8be5\u65b9\u6cd5\u5728\u4e0d\u540c\u7684\u533b\u5b66\u57fa\u51c6<\/mark>\u4e0a\u4f18\u4e8e Solo \u548c Group \u8bbe\u7f6e\u3002\uff08\u6765\u6e90\uff1a\u8bba\u6587\uff09<\/p>\n

\u901a\u8fc7\u7ed3\u5408 MedRAG \u548c\u4e3b\u6301\u4eba\u7684\u8bc4\u5ba1\uff0c\u51c6\u786e\u7387<\/mark>\u53ef\u63d0\u9ad8\u9ad8\u8fbe 11.8%\u3002\u6b64\u5916\uff0c\u8be5\u6846\u67b6\u5bf9\u53c2\u6570\u53d8\u5316\uff08\u5305\u62ec\u6e29\u5ea6\u8c03\u6574\uff09\u7684\u5f39\u6027\u51f8\u663e\u4e86\u5176\u5bf9\u590d\u6742\u533b\u7597\u51b3\u7b56\u4efb\u52a1\u7684\u9002\u5e94\u6027\u3002<\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2404.15155<\/em><\/p>\n

\u76f8\u5173\u62a5\u9053\uff1ahttps:\/\/www.marktechpost.com\/2024\/11\/04\/mdagents-a-dynamic-multi-agent-framework-for-enhanced-medical-decision-making-with-large-language-models\/<\/em><\/p>\n

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