{"id":4760,"date":"2026-01-16T15:08:08","date_gmt":"2026-01-16T07:08:08","guid":{"rendered":"https:\/\/www.15zhi.net\/blog\/?p=4760"},"modified":"2026-01-16T15:08:08","modified_gmt":"2026-01-16T07:08:08","slug":"202601-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-chatdiet-empowering-personalized-nutrition-oriented-food-recommender-chatbots-through-an-llm-augmented-framework","status":"publish","type":"post","link":"https:\/\/www.15zhi.net\/blog\/202601-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-chatdiet-empowering-personalized-nutrition-oriented-food-recommender-chatbots-through-an-llm-augmented-framework\/","title":{"rendered":"202601 \u8bba\u6587\u7814\u8bfb-ChatDiet: Empowering personalized nutrition-oriented food recommender chatbots through an LLM-augmented framework"},"content":{"rendered":"\n

\u6765\u6e90\uff1aElsevier Smart Health
\u4f5c\u8005\uff1aZhongqi Yang\u7b49
\u5355\u4f4d\uff1aUniversity of California
\u53d1\u8868\u65f6\u95f4\uff1a2024 \u5e74 03\u6708<\/p>\n\n\n\n

\u7814\u7a76\u80cc\u666f<\/h2>\n\n\n\n
    \n
  1. \u6838\u5fc3\u95ee\u9898\uff1a\u996e\u98df\u4e0e\u5065\u5eb7\u7684\u7d27\u5bc6\u8054\u7cfb
    \u996e\u98df\u5bf9\u4eba\u7c7b\u5065\u5eb7\u6709\u7740\u6df1\u8fdc\u5f71\u54cd\uff0c\u4e0d\u4ec5\u5173\u4e4e\u6574\u4f53\u798f\u7949\uff0c\u8fd8\u76f4\u63a5\u5f71\u54cd\u75be\u75c5\u7ba1\u7406\u3001\u7761\u7720\u3001\u60c5\u7eea\u548c\u514d\u75ab\u529f\u80fd\u3002
    \u4f8b\u5982\uff0c\u5730\u4e2d\u6d77\u996e\u98df\uff08\u5bcc\u542b\u852c\u679c\u3001\u8c37\u7269\uff0c\u4f4e\u8102\u80aa\uff09\u88ab\u8bc1\u660e\u5bf9\u80a0\u9053\u5065\u5eb7\u81f3\u5173\u91cd\u8981\u3002<\/li>\n<\/ol>\n\n\n\n
      \n
    1. \u8425\u517b\u5bfc\u5411\u7684\u98df\u7269\u63a8\u8350\u7cfb\u7edf\uff1a
      \u7f3a\u4e4f\u771f\u6b63\u7684\u4e2a\u6027\u5316\u3001\u7f3a\u4e4f\u53ef\u89e3\u91ca\u6027\u3001\u7f3a\u4e4f\u4ea4\u4e92\u6027\u3002<\/li>\n\n\n\n
    2. LLMs\u7684\u673a\u9047\u4e0e\u6311\u6218\uff1a
      LLMs\uff08\u5982ChatGPT\uff09\u5929\u751f\u5177\u6709\u53ef\u89e3\u91ca\u6027\u548c\u4ea4\u4e92\u6027\u3002\u5b83\u4eec\u53ef\u4ee5\u50cf\u804a\u5929\u673a\u5668\u4eba\u4e00\u6837\uff0c\u7528\u81ea\u7136\u8bed\u8a00\u6e05\u6670\u5730\u89e3\u91ca\u539f\u56e0\uff0c\u5e76\u8fdb\u884c\u591a\u8f6e\u5bf9\u8bdd\u3002<\/li>\n<\/ol>\n\n\n\n

      \u4e3b\u8981\u6846\u67b6<\/h2>\n\n\n\n
      \"\"<\/figure>\n\n\n\n

      ChatDiet\u662f\u4e00\u4e2aLLM\u589e\u5f3a\u578b\u6846\u67b6\uff0c\u5b83\u901a\u8fc7\u4e00\u4e2a\u540d\u4e3a\u201cOrchestrator\uff08\u534f\u8c03\u5668\uff09\u201d\u7684\u6838\u5fc3\u6a21\u5757\uff0c\u5c06\u4e2a\u4eba\u6a21\u578b (Personal Model) \u548c\u7fa4\u4f53\u6a21\u578b (Population Model) \u7684\u4fe1\u606f\u6574\u5408\u8d77\u6765\uff0c\u518d\u8f93\u5165\u7ed9LLM\uff0c\u6700\u7ec8\u751f\u6210\u4e2a\u6027\u5316\u7684\u56de\u7b54\u3002<\/p>\n\n\n\n

        \n
      1. \u5de5\u4f5c\u6d41\u7a0b\u603b\u7ed3
        \u7528\u6237\u63d0\u95ee \u2192 \u534f\u8c03\u5668\u89e3\u6790\u95ee\u9898 \u2192 \u534f\u8c03\u5668\u4ece\u4e2a\u4eba\u6a21\u578b\u68c0\u7d22\u76f8\u5173\u56e0\u679c\u6548\u5e94 \u2192 \u534f\u8c03\u5668\u4ece\u7fa4\u4f53\u6a21\u578b\u68c0\u7d22\u542b\u6709\u6240\u9700\u8425\u517b\u7d20\u7684\u98df\u7269 \u2192 \u534f\u8c03\u5668\u5c06\u6240\u6709\u4fe1\u606f\u6253\u5305\u6210\u7ed3\u6784\u5316\u63d0\u793a \u2192 LLM\u6839\u636e\u63d0\u793a\u751f\u6210\u6700\u7ec8\u7684\u3001\u5e26\u6709\u9010\u6b65\u89e3\u91ca\u7684\u56de\u7b54\u3002<\/li>\n<\/ol>\n\n\n\n
          \n
        1. \u56db\u5927\u6838\u5fc3\u7ec4\u4ef6\u8be6\u89e3\uff1a<\/li>\n<\/ol>\n\n\n\n

          A. \u534f\u8c03\u5668 (Orchestrator)\uff1a\u68c0\u7d22 (Retrieving)\u3001\u8f6c\u5f55 (Transcribing)\u3001\u63d0\u793a\u5de5\u7a0b (Prompt Engineering)<\/p>\n\n\n\n

          B. \u4e2a\u4eba\u6a21\u578b (Personal Model)\uff1a\u56e0\u679c\u53d1\u73b0 (Causal Discovery) + \u56e0\u679c\u63a8\u65ad (Causal Inference)\uff1b<\/p>\n\n\n\n

          C. \u7fa4\u4f53\u6a21\u578b (Population Model)\uff1a\u4f5c\u4e3a\u4e00\u4e2a\u201c\u77e5\u8bc6\u52a0\u8f7d\u5668\u201d\uff0c\u76f4\u63a5\u4ece\u5927\u578b\u516c\u5171\u98df\u7269\u6570\u636e\u5e93\uff08\u5982Cronometer, Nutritionix\uff09\u4e2d\u52a0\u8f7d\u98df\u7269\u7684\u8be6\u7ec6\u8425\u517b\u6210\u5206\u8868\uff1b<\/p>\n\n\n\n

          D. \u751f\u6210\u5f0f\u54cd\u5e94 (Generative Response)\uff1a\u8f93\u51fa\uff1a\u4e00\u4e2a\u4e2a\u6027\u5316\u3001\u53ef\u89e3\u91ca\u3001\u81ea\u7136\u6d41\u7545\u7684\u5bf9\u8bdd\u56de\u590d\uff0c\u5411\u7528\u6237\u63a8\u8350\u5177\u4f53\u98df\u7269\u5e76\u89e3\u91ca\u539f\u56e0\u3002<\/p>\n\n\n\n

          \u4e2a\u4eba\u6a21\u578b (Personal Model)<\/p>\n\n\n\n

          \u76ee\u6807\uff1a\u6355\u6349\u8be5\u7528\u6237\u72ec\u4e00\u65e0\u4e8c\u7684\u8425\u517b-\u5065\u5eb7\u5173\u7cfb\u3002
          \u6838\u5fc3\u6280\u672f\uff1a\u56e0\u679c\u53d1\u73b0 + \u56e0\u679c\u63a8\u65ad<\/p>\n\n\n\n

          \u56e0\u679c\u53d1\u73b0\uff1a\u4f7f\u7528\u7b97\u6cd5\uff08\u5982SAM\uff09\u5206\u6790\u7528\u6237\u7684\u957f\u671f\u4e2a\u4eba\u6570\u636e\uff08\u996e\u98df\u65e5\u5fd7\u3001\u7761\u7720\u3001\u5fc3\u7387\u7b49\uff09\uff0c\u81ea\u52a8\u6784\u5efa\u4e00\u4e2a\u56e0\u679c\u56fe \uff0c\u63ed\u793a\u54ea\u4e9b\u8425\u517b\u7d20\u4f1a\u5f71\u54cd\u54ea\u4e9b\u5065\u5eb7\u6307\u6807\u3002
          \u56e0\u679c\u63a8\u65ad\uff1a\u5728\u56e0\u679c\u56fe\u7684\u57fa\u7840\u4e0a\uff0c\u8ba1\u7b97\u51fa\u5177\u4f53\u7684\u4e2a\u4f53\u5316\u5904\u7406\u6548\u5e94 (Individual Treatment Effect, ITE)\u3002\u4f8b\u5982\uff0c\u201c\u5bf9\u8fd9\u4f4d\u7528\u6237\u800c\u8a00\uff0c\u6bcf\u589e\u52a01mg\u7684\u7ef4\u751f\u7d20B1\uff0c\u5176\u6df1\u5ea6\u7761\u7720\u65f6\u957f\u5e73\u5747\u589e\u52a014.3\u5206\u949f\u201d\u3002<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n

          \u5b9e\u9a8c<\/h2>\n\n\n\n

          \u6570\u636e\u96c6 (Dataset)
          N-of-1 \u771f\u5b9e\u6570\u636e\u96c6\uff1a
          \u6765\u6e90\uff1a\u4e00\u4f4d\u53c2\u4e0e\u8005\u957f\u8fbe\u4e09\u5e74\u7684\u4e2a\u4eba\u6570\u636e\u3002
          \u6570\u636e\u7c7b\u578b\uff1a
          \u996e\u98df\uff1a\u901a\u8fc7Cronometer App\u8bb0\u5f55\u7684\u6bcf\u65e5\u6444\u5165\u70ed\u91cf\u53ca\u5b8f\/\u5fae\u91cf\u8425\u517b\u7d20\u3002
          \u5065\u5eb7\u6307\u6807\uff1a\u901a\u8fc7Oura\u667a\u80fd\u6212\u6307\u6536\u96c6\u7684\u7761\u7720\u3001\u5fc3\u7387\u3001\u6d3b\u52a8\u91cf\u7b49\uff1b\u901a\u8fc7Arboleaf\u4f53\u8102\u79e4\u6536\u96c6\u7684\u8eab\u4f53\u6210\u5206\u6570\u636e\uff1bApple Health\u4e2d\u7684\u8840\u538b\u7b49\u3002
          \u5408\u6210\u6570\u636e\u96c6 (Synthetic Dataset)\uff1a
          \u76ee\u7684\uff1a\u7531\u4e8eN-of-1\u6570\u636e\u53ea\u6709\u4e00\u4e2a\u6837\u672c\uff0c\u65e0\u6cd5\u8fdb\u884c\u5927\u89c4\u6a21\u5b9a\u91cf\u8bc4\u4f30\u3002\u56e0\u6b64\uff0c\u57fa\u4e8e\u771f\u5b9e\u6570\u636e\u7684\u5206\u5e03\u548c\u56e0\u679c\u56fe\uff0c\u5408\u6210\u4e86100\u4e2a\u865a\u62df\u53c2\u4e0e\u8005\u7684\u6570\u636e\uff0c\u4ee5\u6269\u5927\u8bc4\u4f30\u89c4\u6a21\u3002<\/p>\n\n\n\n

          \u63a8\u8350\u6709\u6548\u6027\u6d4b\u8bd5<\/p>\n\n\n\n

          \uff081\uff09\u65b9\u6cd5\uff1a
          \u6784\u9020\u6807\u51c6\u5316\u67e5\u8be2\uff1a\u201c\u8bf7\u63a8\u8350\u4e00\u79cd\u98df\u7269\u6765\u63d0\u9ad8[\u76ee\u6807\u5065\u5eb7\u6307\u6807]\u201d\uff0c\u5176\u4e2d\u76ee\u6807\u6307\u6807\u5305\u62ec\u5fc3\u7387\u53d8\u5f02\u6027(HRV)\u3001\u6574\u4f53\u7761\u7720\u8d28\u91cf\u3001REM\u7761\u7720\u65f6\u957f\u3001\u6df1\u5ea6\u7761\u7720\u65f6\u957f\u3002
          \u5bf9100\u4e2a\u5408\u6210\u7528\u6237\uff0c\u6bcf\u4e2a\u6307\u6807\u751f\u6210100\u4e2a\u67e5\u8be2\uff0c\u5171400\u4e2a\u95ee\u7b54\u5bf9\u3002
          \u4eba\u5de5\u8bc4\u4f30\uff1a\u68c0\u67e5ChatDiet\u7684\u56de\u590d\u662f\u5426\uff1a
          \u63a8\u8350\u4e86\u6b63\u786e\u7684\u98df\u7269\uff08\u542b\u6709\u5bf9\u76ee\u6807\u6307\u6807\u6709\u6b63\u9762\u4e2a\u4eba\u6548\u5e94\u7684\u8425\u517b\u7d20\uff09\u3002
          \u7ed9\u51fa\u7684\u89e3\u91ca\u4e0e\u4e2a\u4eba\u6a21\u578b\u8ba1\u7b97\u51fa\u7684\u8425\u517b\u6548\u5e94\u4e00\u81f4\u3002
          \u8bc4\u4f30\u6307\u6807\uff1a\u63a8\u8350\u6709\u6548\u6027\u6bd4\u7387 (Recommendation Effectiveness Ratio, RER) = \u6b63\u786e\u63a8\u8350\u6570 \/ \u603b\u63a8\u8350\u6570\u3002<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n

          \u5b9a\u6027\u8bc4\u4f30\uff1a\u4e09\u5927\u6838\u5fc3\u4f18\u52bf\u6f14\u793a<\/p>\n\n\n\n

          \uff081\uff09\u53ef\u89e3\u91ca\u6027 (Explainability)
          \u5c55\u793a\u5bf9\u8bdd\u793a\u4f8b\uff1a\u5f53\u7528\u6237\u8be2\u95ee\u5982\u4f55\u6539\u5584REM\u7761\u7720\u65f6\uff0cChatDiet\u4e0d\u4ec5\u63a8\u8350\u4e86\u201c\u674f\u4ec1\u201d\uff0c\u8fd8\u5206\u6b65\u89e3\u91ca\uff1a\u201c\u56e0\u4e3a\u60a8\u7684\u6570\u636e\u663e\u793a\uff0c\u7ef4\u751f\u7d20E\u3001\u7f2c\u6c28\u9178\u548c\u86cb\u767d\u8d28\u5bf9\u60a8\u7684REM\u7761\u7720\u6709\u6b63\u9762\u5f71\u54cd\uff0c\u800c\u674f\u4ec1\u5bcc\u542b\u7ef4\u751f\u7d20E\u3002\u201d<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n

          \uff082\uff09\u4e2a\u6027\u5316 (Personalization)
          ChatDiet\uff08\u542f\u7528\u4e2a\u4eba\u6a21\u578b\uff09\uff1a\u5bf9\u4e8e\u4e00\u4e2aOmega-3\u5bf9\u5176REM\u7761\u7720\u6709\u8d1f\u9762\u5f71\u54cd\u7684\u7528\u6237\uff0c\u5373\u4f7f\u4e09\u6587\u9c7c\u5bcc\u542bOmega-3\uff0cChatDiet\u4e5f\u4f1a\u56e0\u4e3a\u5176\u9ad8\u86cb\u767d\u542b\u91cf\uff08\u5bf9\u7528\u6237\u6709\u76ca\uff09\u800c\u8c28\u614e\u63a8\u8350\uff0c\u5e76\u89e3\u91ca\u6743\u8861\u3002\u201d<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n

          \uff083\uff09\u4ea4\u4e92\u6027 (Interactivity)
          \u5c55\u793a\u591a\u8f6e\u5bf9\u8bdd\u793a\u4f8b\uff1a
          \u7528\u6237\u521d\u6b21\u63d0\u95ee\u540e\uff0c\u89c9\u5f97\u89e3\u91ca\u4e0d\u591f\u8be6\u7ec6\uff0c\u8ffd\u95ee\u201c\u80fd\u518d\u8be6\u7ec6\u89e3\u91ca\u4e00\u4e0b\u5417\uff1f\u201d \u2192 ChatDiet\u80fd\u63d0\u4f9b\u66f4\u6df1\u5165\u7684\u89e3\u7b54\u3002
          \u7528\u6237\u8868\u793a\u201c\u6211\u4e0d\u559c\u6b22\u5403\u674f\u4ec1\u201d \u2192 ChatDiet\u80fd\u7acb\u523b\u52a8\u6001\u8c03\u6574\uff0c\u63a8\u8350\u53e6\u4e00\u4e2a\u540c\u6837\u5bcc\u542b\u6240\u9700\u8425\u517b\u7d20\u7684\u66ff\u4ee3\u54c1\u3002<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n

          \u603b\u7ed3\u4e0e\u7efc\u5408\u5bf9\u9f50\u601d\u8003<\/h2>\n\n\n\n

          \uff08\u4e00\uff09\u8bba\u6587\u6838\u5fc3\u5185\u5bb9<\/p>\n\n\n\n

          \u8fd9\u7bc7\u8bba\u6587\u63d0\u51fa ChatDiet\uff0c\u628a\u201c\u4e2a\u4f53\u5316\u8bc1\u636e\u201d\u548c\u201c\u901a\u7528\u8425\u517b\u77e5\u8bc6\u201d\u5148\u6574\u7406\u597d\uff0c\u518d\u4ea4\u7ed9 LLM \u7528\u81ea\u7136\u8bed\u8a00\u8f93\u51fa\u63a8\u8350\u4e0e\u89e3\u91ca\uff0cLLM \u4e3b\u8981\u627f\u62c5\u201c\u5bf9\u8bdd + \u89e3\u91ca\u201d\u7684\u89d2\u8272\uff0c\u800c\u4e0d\u662f\u7aef\u5230\u7aef\u51b3\u7b56\u5668\u3002\u5176\u6838\u5fc3\u8d21\u732e\u5305\u62ec\uff1a
          \u7528\u56e0\u679c\u63a8\u65ad\u6784\u5efa\u201c\u6570\u5b57\u8425\u517b\u5b6a\u751f\u4f53\u201d\u5b9e\u73b0\u6df1\u5ea6\u4e2a\u6027\u5316\uff1a\u5229\u7528\u56e0\u679c\u53d1\u73b0 \u548c \u56e0\u679c\u63a8\u65ad\u6280\u672f\uff0c\u4ece\u7528\u6237\u957f\u671f\u7684\u591a\u6a21\u6001\u5065\u5eb7\u6570\u636e\uff08\u996e\u98df\u3001\u7761\u7720\u3001\u5fc3\u7387\u7b49\uff09\u4e2d\u81ea\u52a8\u5b66\u4e60\u4e2a\u4f53\u4e13\u5c5e\u7684\u201c\u8425\u517b\u2013\u5065\u5eb7\u201d\u56e0\u679c\u56fe\u3002\u5c06\u8fd9\u4e9b\u91cf\u5316\u3001\u53ef\u89e3\u91ca\u7684\u4e2a\u4eba\u56e0\u679c\u77e5\u8bc6\u4f5c\u4e3a\u7ed3\u6784\u5316\u8f93\u5165\u4f7fLLM\u7684\u63a8\u8350\u4e25\u683c\u951a\u5b9a\u5728\u7528\u6237\u81ea\u8eab\u6570\u636e\u4e0a\uff0c\u800c\u975e\u901a\u7528\u77e5\u8bc6\u3002
          \u63d0\u51fa\u201c\u534f\u8c03\u5668\uff08Orchestrator\uff09\u201d\u67b6\u6784\uff0c\u6709\u6548\u7ea6\u675fLLM\u884c\u4e3a\uff1a\u8bbe\u8ba1\u4e86\u4e00\u4e2a\u975e\u751f\u6210\u5f0f\u7684\u4e2d\u95f4\u63a7\u5236\u6a21\u5757\uff0c\u901a\u8fc7\u68c0\u7d22\u3001\u8f6c\u5f55\u3001\u63d0\u793a\u5de5\u7a0b\u6765\u63d0\u5347LLM\u8f93\u51fa\u7684\u51c6\u786e\u6027\u3001\u4e00\u81f4\u6027\u548c\u53ef\u89e3\u91ca\u6027\u3002<\/p>\n\n\n\n

          \uff08\u4e8c\uff09\u4e09\u7ef4\u5ea6\u5bf9\u9f50\u601d\u8003<\/p>\n\n\n\n

          1.0 \u6280\u672f\u521b\u65b0-\u903b\u8f91\u601d\u7ef4\u63a8\u7406\u6846\u67b6
          \u8fd9\u7bc7\u8bba\u6587\u8bc1\u5b9e\uff1a\u628a\u53ef\u4f9d\u8d56\u7684\u8bc1\u636e\u5148\u6784\u9020\u51fa\u6765\uff08\u4e2a\u4eba\u56e0\u679c\u6548\u5e94\u3001\u98df\u7269\u8425\u517b\u6210\u5206\uff09\uff0c\u518d\u8ba9 LLM \u5728\u8fd9\u4e2a\u8bc1\u636e\u7a7a\u95f4\u91cc\u8f93\u51fa\u3002\u53ef\u4ee5\u501f\u9274\u5176\u601d\u8def\uff0c\u5728\u6bd4\u9009\u63a8\u7406\u4e2d\uff1a\u4e0d\u5e94\u8be5\u8ba9 LLM \u201c\u81ea\u7531\u63a8\u8350\u201d\uff0c\u800c\u662f\u8ba9\u5b83\u5728\u7ed3\u6784\u5316\u7ef4\u5ea6\u4e2d\u505a\u51fa\u5224\u65ad \u3002\u53e6\u5916\uff0c\u5728\u8bc4\u4f30\u90e8\u5206ChatDiet \u6ca1\u8d70\u201c\u62d4\u6a21\u5757\u201d\u7684\u4f20\u7edf\u6d88\u878d\uff0c\u800c\u662f\u56f4\u7ed5\u6838\u5fc3\u98ce\u9669\u70b9\u505a\u9a8c\u8bc1\uff0c\u81ea\u5df1\u5b9e\u9a8c\u90e8\u5206\u4e5f\u5b66\u4e60\u8fd9\u79cd\u504f\u5411\u8bca\u65ad\u578b\u9a8c\u8bc1\u3002
          2.1 \u6280\u672f\u76ee\u6807-\u4e13\u4e1a\u624b\u518c\u516c\u4f17\u670d\u52a1
          \u6784\u5efa\u51fa\u9ad8\u5bf9\u6bd4\u6bd4\u8f83\u5bf9\uff1a\u901a\u8fc7\u6846\u67b6\u7684\u68c0\u7d22-\u6392\u5e8f-LLM\u63a8\u7406\u7684pipeline\uff0c\u5c06\u9ad8\u8d28\u91cf\u7684\u5065\u5eb7\u5019\u9009\u4ea7\u54c1\u9001\u5165\u6bd4\u8f83\u5bf9\u63a8\u7406\u90e8\u5206\uff0c\u6784\u5efa\uff08\u951a\u70b9\u98df\u8c31\u3001\u5019\u9009\u4ea7\u54c11\uff0c\u5019\u9009\u4ea7\u54c12\uff09\u7684\u8fed\u4ee3\u903b\u8f91\u6bd4\u9009\uff0c\u6700\u7ec8\u9009\u62e9\u51fa\u6700\u4f18\u98df\u54c1\uff0c\u8fd9\u7bc7\u8bba\u6587\u662f\u201cLLM + evidence grounding \u505a\u89e3\u91ca\u201d\uff0c\u8fd9\u4e5f\u66f4\u8bc1\u660e\u4e86\u98df\u8c31\u9886\u57df\u591a\u76ee\u6807\u51b2\u7a81\u4e0b\u7684\u51b3\u7b56\u7684\u610f\u4e49\u3002
          3.1 \u573a\u666f\u529f\u80fd-\u98df\u517b\u901a
          \u5728pk\u6bd4\u9009\u8fd9\u4e2a\u90e8\u5206\u8fdb\u884c\u5e94\u7528\uff0c\u9488\u5bf9\u7528\u6237\u9009\u4e2d\u7684\u98df\u54c1\uff0c\u5728\u7cfb\u7edf\u4e2d\u81ea\u52a8\u63a8\u51fa\u7ed3\u5408\u7528\u6237\u4e2a\u6027\u5316\u7684\u66f4\u5065\u5eb7\u4ea7\u54c1\uff0c\u5e76\u5c55\u793a\u51fa\u5bf9\u6bd4\u6027\u89e3\u91ca\u8bf4\u660e\u63d0\u5347\u63a8\u8350\u6548\u679c\u3002<\/p>\n\n\n\n

          <\/p>\n","protected":false},"excerpt":{"rendered":"

          \u6765\u6e90\uff1aElsevier Smart Health\u4f5c\u8005\uff1aZhongqi Yang\u7b49\u5355\u4f4d\uff1aUniversity o […]<\/p>\n","protected":false},"author":60,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4760","post","type-post","status-publish","format-standard","hentry","category-events"],"_links":{"self":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts\/4760","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/users\/60"}],"replies":[{"embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/comments?post=4760"}],"version-history":[{"count":1,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts\/4760\/revisions"}],"predecessor-version":[{"id":4767,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts\/4760\/revisions\/4767"}],"wp:attachment":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/media?parent=4760"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/categories?post=4760"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/tags?post=4760"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}