{"id":157,"date":"2023-10-19T17:35:26","date_gmt":"2023-10-19T09:35:26","guid":{"rendered":"http:\/\/ai.gitpp.com\/?p=157"},"modified":"2023-10-19T19:45:36","modified_gmt":"2023-10-19T11:45:36","slug":"%e5%9c%a8github%e4%b8%8a%ef%bc%8c%e6%9c%89%e8%ae%b8%e5%a4%9a%e4%ba%ba%e5%b7%a5%e6%99%ba%e8%83%bd%e6%8a%80%e6%9c%af%e5%9c%a8%e5%8c%bb%e7%96%97%e8%a1%8c%e4%b8%9a%e7%9a%84%e5%ba%94%e7%94%a8%e9%a1%b9","status":"publish","type":"post","link":"http:\/\/ai.gitpp.com\/index.php\/2023\/10\/19\/%e5%9c%a8github%e4%b8%8a%ef%bc%8c%e6%9c%89%e8%ae%b8%e5%a4%9a%e4%ba%ba%e5%b7%a5%e6%99%ba%e8%83%bd%e6%8a%80%e6%9c%af%e5%9c%a8%e5%8c%bb%e7%96%97%e8%a1%8c%e4%b8%9a%e7%9a%84%e5%ba%94%e7%94%a8%e9%a1%b9\/","title":{"rendered":"\u5728GitHub\u4e0a\uff0c\u6709\u8bb8\u591a\u4eba\u5de5\u667a\u80fd\u6280\u672f\u5728\u533b\u7597\u884c\u4e1a\u7684\u5e94\u7528\u9879\u76ee"},"content":{"rendered":"\n

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\u5728GitHub\u4e0a\uff0c\u6709\u8bb8\u591a\u4eba\u5de5\u667a\u80fd\u6280\u672f\u5728\u533b\u7597\u884c\u4e1a\u7684\u5e94\u7528\u9879\u76ee\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u9879\u76ee\u793a\u4f8b\uff1a<\/p>\n\n\n\n

    \n
  1. DeepRadiology: \u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u533b\u5b66\u56fe\u50cf\u5206\u6790\u7684\u6df1\u5ea6\u5b66\u4e60\u9879\u76ee\u3002\u5b83\u4f7f\u7528\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\uff08CNN\uff09\u548c\u5176\u4ed6\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\uff0c\u63d0\u4f9b\u4e86\u5bf9\u533b\u5b66\u5f71\u50cf\u8fdb\u884c\u5206\u5272\u3001\u5206\u7c7b\u548c\u68c0\u6d4b\u7684\u529f\u80fd\u3002<\/li>\n\n\n\n
  2. Med3D: \u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u533b\u5b66\u56fe\u50cf\u5206\u6790\u548c\u53ef\u89c6\u5316\u7684\u9879\u76ee\u3002\u5b83\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\uff0c\u63d0\u4f9b\u4e86\u5bf9\u533b\u5b66\u5f71\u50cf\u8fdb\u884c\u4e09\u7ef4\u91cd\u5efa\u3001\u5206\u5272\u548c\u6d4b\u91cf\u7684\u529f\u80fd\u3002<\/li>\n\n\n\n
  3. MIMIC-III: \u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u533b\u7597\u6570\u636e\u5206\u6790\u7684\u9879\u76ee\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5927\u89c4\u6a21\u7684\u533b\u7597\u6570\u636e\u5e93\uff0c\u5305\u542b\u4e86\u4e34\u5e8a\u6570\u636e\u3001\u751f\u7406\u6570\u636e\u548c\u533b\u5b66\u5f71\u50cf\u7b49\u591a\u4e2a\u65b9\u9762\u7684\u4fe1\u606f\uff0c\u53ef\u4ee5\u7528\u4e8e\u8fdb\u884c\u533b\u5b66\u7814\u7a76\u548c\u7b97\u6cd5\u5f00\u53d1\u3002<\/li>\n\n\n\n
  4. ClinicalBERT: \u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u4e34\u5e8a\u6587\u672c\u5206\u6790\u7684\u9879\u76ee\u3002\u5b83\u57fa\u4e8e\u9884\u8bad\u7ec3\u7684BERT\u6a21\u578b\uff0c\u63d0\u4f9b\u4e86\u5bf9\u4e34\u5e8a\u6587\u672c\u8fdb\u884c\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u5173\u7cfb\u62bd\u53d6\u548c\u60c5\u611f\u5206\u6790\u7b49\u529f\u80fd\u3002<\/li>\n\n\n\n
  5. DeepPatient: \u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u4e2a\u6027\u5316\u533b\u7597\u7684\u6df1\u5ea6\u5b66\u4e60\u9879\u76ee\u3002\u5b83\u4f7f\u7528\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\uff0c\u5206\u6790\u60a3\u8005\u7684\u4e34\u5e8a\u6570\u636e\uff0c\u63d0\u4f9b\u4e2a\u6027\u5316\u7684\u8bca\u65ad\u548c\u6cbb\u7597\u5efa\u8bae\u3002<\/li>\n\n\n\n
  6. AI-Radiology: \u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u653e\u5c04\u5f71\u50cf\u5206\u6790\u7684\u4eba\u5de5\u667a\u80fd\u9879\u76ee\u3002\u5b83\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u6280\u672f\uff0c\u81ea\u52a8\u68c0\u6d4b\u548c\u8bca\u65ad\u653e\u5c04\u5f71\u50cf\u4e2d\u7684\u75be\u75c5\u548c\u5f02\u5e38\u3002<\/li>\n<\/ol>\n\n\n\n

    \u8fd9\u4e9b\u9879\u76ee\u63d0\u4f9b\u4e86\u4e0d\u540c\u65b9\u9762\u7684\u4eba\u5de5\u667a\u80fd\u6280\u672f\u5728\u533b\u7597\u884c\u4e1a\u7684\u5e94\u7528\u793a\u4f8b\uff0c\u6db5\u76d6\u4e86\u533b\u5b66\u56fe\u50cf\u5206\u6790\u3001\u4e34\u5e8a\u6570\u636e\u5206\u6790\u3001\u4e2a\u6027\u5316\u533b\u7597\u7b49\u591a\u4e2a\u9886\u57df\u3002\u60a8\u53ef\u4ee5\u5728GitHub\u4e0a\u641c\u7d22\u8fd9\u4e9b\u9879\u76ee\uff0c\u4e86\u89e3\u66f4\u591a\u5173\u4e8e\u5b83\u4eec\u7684\u4fe1\u606f\uff0c\u5e76\u83b7\u53d6\u6e90\u4ee3\u7801\u548c\u6587\u6863\u3002\u8bf7\u6ce8\u610f\uff0c\u9879\u76ee\u7684\u8d28\u91cf\u548c\u6210\u719f\u5ea6\u53ef\u80fd\u4f1a\u6709\u6240\u4e0d\u540c\uff0c\u5efa\u8bae\u60a8\u4ed4\u7ec6\u8bc4\u4f30\u548c\u9a8c\u8bc1\u8fd9\u4e9b\u9879\u76ee\u7684\u9002\u7528\u6027\u3002<\/p>\n\n\n\n

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

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

    \u5728Github\u4e0a\u6709\u8bb8\u591a\u836f\u7269\u7814\u53d1\u9886\u57df\u7684\u5f00\u6e90\u9879\u76ee\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e9b\u793a\u4f8b\uff1a<\/p>\n\n\n\n

      \n
    1. MolVS\uff1a\u8fd9\u4e2a\u9879\u76ee\u662f\u4e00\u4e2a\u7528\u4e8e\u5206\u5b50\u9a8c\u8bc1\u548c\u6807\u51c6\u5316\u7684Python\u5e93\uff0c\u53ef\u7528\u4e8e\u836f\u7269\u53d1\u73b0\u548c\u8bbe\u8ba1\u7814\u7a76\u3002<\/li>\n\n\n\n
    2. RDKit\uff1a\u8fd9\u4e2a\u9879\u76ee\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u5206\u5b50\u5de5\u5177\u5305\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u7528\u4e8e\u5206\u5b50\u5efa\u6a21\u548c\u836f\u7269\u53d1\u73b0\u7684\u529f\u80fd\uff0c\u5305\u62ec\u5206\u5b50\u63cf\u8ff0\u7b26\u8ba1\u7b97\u3001\u836f\u7269\u5e93\u7b5b\u9009\u7b49\u3002<\/li>\n\n\n\n
    3. OpenChem\uff1a\u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u5206\u5b50\u673a\u5668\u5b66\u4e60\u7684Python\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u5f00\u653e\u5316\u5b66\u548c\u5206\u5b50\u4fe1\u606f\u5b66\u5de5\u5177\uff0c\u7528\u4e8e\u836f\u7269\u53d1\u73b0\u548c\u8bbe\u8ba1\u7814\u7a76\u3002<\/li>\n\n\n\n
    4. Cheminformatics-Toolkit\uff1a\u8fd9\u4e2a\u9879\u76ee\u662f\u4e00\u4e2a\u7528\u4e8e\u5316\u5b66\u4fe1\u606f\u5b66\u548c\u836f\u7269\u53d1\u73b0\u7684Python\u5de5\u5177\u5305\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u5206\u5b50\u5efa\u6a21\u548c\u5206\u6790\u7684\u529f\u80fd\u3002<\/li>\n\n\n\n
    5. AutoDock Vina\uff1a\u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u5206\u5b50\u5bf9\u63a5\u548c\u865a\u62df\u7b5b\u9009\u7684\u5f00\u6e90\u8f6f\u4ef6\uff0c\u7528\u4e8e\u9884\u6d4b\u836f\u7269\u5206\u5b50\u4e0e\u9776\u70b9\u4e4b\u95f4\u7684\u76f8\u4e92\u4f5c\u7528\u3002<\/li>\n\n\n\n
    6. Cheminformatics Workflows\uff1a\u8fd9\u4e2a\u9879\u76ee\u662f\u4e00\u4e2a\u7528\u4e8e\u836f\u7269\u53d1\u73b0\u548c\u836f\u7269\u5f00\u53d1\u6d41\u7a0b\u7684\u5f00\u6e90\u5de5\u4f5c\u6d41\u6846\u67b6\uff0c\u57fa\u4e8eKnime\u5e73\u53f0\u3002<\/li>\n<\/ol>\n\n\n\n

      \u4ee5\u4e0a\u4ec5\u662f\u4e00\u4e9b\u793a\u4f8b\uff0cGithub\u4e0a\u8fd8\u6709\u8bb8\u591a\u5176\u4ed6\u836f\u7269\u7814\u53d1\u9886\u57df\u7684\u5f00\u6e90\u9879\u76ee\uff0c\u6db5\u76d6\u4e86\u5206\u5b50\u5efa\u6a21\u3001\u836f\u7269\u7b5b\u9009\u3001\u5206\u5b50\u673a\u5668\u5b66\u4e60\u7b49\u4e0d\u540c\u65b9\u9762\u7684\u5de5\u5177\u548c\u5e93\u3002<\/p>\n\n\n\n

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

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

      \u4ee5\u4e0b\u662f\u4e00\u4e9b\u5728GitHub\u4e0a\u7684\u533b\u5b66\u5f71\u50cf\u5206\u6790\u7684\u5f00\u6e90\u9879\u76ee\uff1a<\/p>\n\n\n\n

        \n
      1. TensorFlow Medical: \u4e00\u4e2a\u57fa\u4e8eTensorFlow\u6846\u67b6\u7684\u533b\u5b66\u5f71\u50cf\u5206\u6790\u5e93\uff0c\u5305\u62ec\u5404\u79cd\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u548c\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u5b9e\u73b0\uff0c\u7528\u4e8e\u56fe\u50cf\u5206\u7c7b\u3001\u5206\u5272\u548c\u751f\u6210\u7b49\u4efb\u52a1\u3002<\/li>\n\n\n\n
      2. Medical Imaging Analysis Toolkits (MedPy): \u4e00\u4e2a\u7528\u4e8e\u533b\u5b66\u5f71\u50cf\u5206\u6790\u7684Python\u5e93\uff0c\u63d0\u4f9b\u4e86\u5404\u79cd\u5904\u7406\u3001\u5206\u5272\u548c\u7279\u5f81\u63d0\u53d6\u7684\u51fd\u6570\uff0c\u652f\u6301\u5e38\u89c1\u7684\u533b\u5b66\u56fe\u50cf\u683c\u5f0f\u3002<\/li>\n\n\n\n
      3. Radiomics: \u4e00\u4e2a\u7528\u4e8e\u63d0\u53d6\u653e\u5c04\u5b66\u7279\u5f81\u7684\u5f00\u6e90\u8f6f\u4ef6\u5e93\uff0c\u7528\u4e8e\u4ece\u533b\u5b66\u5f71\u50cf\u4e2d\u63d0\u53d6\u5b9a\u91cf\u7684\u5f62\u6001\u5b66\u548c\u7eb9\u7406\u7279\u5f81\uff0c\u7528\u4e8e\u8bca\u65ad\u548c\u9884\u6d4b\u3002<\/li>\n\n\n\n
      4. NiftyNet: \u4e00\u4e2a\u57fa\u4e8eTensorFlow\u7684\u5f00\u6e90\u6df1\u5ea6\u5b66\u4e60\u5e73\u53f0\uff0c\u4e13\u95e8\u7528\u4e8e\u533b\u5b66\u5f71\u50cf\u5206\u6790\uff0c\u5305\u62ec\u56fe\u50cf\u5206\u5272\u3001\u5206\u7c7b\u548c\u751f\u6210\u7b49\u4efb\u52a1\u3002<\/li>\n\n\n\n
      5. MONAI: \u4e00\u4e2a\u7528\u4e8e\u533b\u5b66\u5f71\u50cf\u5206\u6790\u7684\u5f00\u6e90PyTorch\u5e93\uff0c\u5305\u62ec\u6570\u636e\u52a0\u8f7d\u3001\u9884\u5904\u7406\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u7b49\u529f\u80fd\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e9b\u7528\u4e8e\u533b\u5b66\u5f71\u50cf\u5206\u6790\u7684\u9884\u8bad\u7ec3\u6a21\u578b\u3002<\/li>\n\n\n\n
      6. 3D Slicer: \u4e00\u4e2a\u5f00\u6e90\u7684\u533b\u5b66\u5f71\u50cf\u5904\u7406\u8f6f\u4ef6\uff0c\u63d0\u4f9b\u4e86\u5148\u8fdb\u7684\u56fe\u50cf\u5206\u5272\u3001\u53ef\u89c6\u5316\u548c\u5206\u6790\u5de5\u5177\uff0c\u652f\u6301\u591a\u79cd\u533b\u5b66\u56fe\u50cf\u6570\u636e\u683c\u5f0f\u3002<\/li>\n<\/ol>\n\n\n\n

        \u8fd9\u53ea\u662f\u4e00\u90e8\u5206\u5728GitHub\u4e0a\u53ef\u7528\u7684\u533b\u5b66\u5f71\u50cf\u5206\u6790\u7684\u5f00\u6e90\u9879\u76ee\uff0c\u8fd8\u6709\u8bb8\u591a\u5176\u4ed6\u9879\u76ee\u4e5f\u503c\u5f97\u63a2\u7d22\u3002<\/p>\n\n\n\n

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

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

        \u4ee5\u4e0b\u662f\u4e00\u4e9b\u4e34\u5e8a\u51b3\u7b56\u652f\u6301\u7684\u5f00\u6e90\u9879\u76ee\u5728GitHub\u4e0a\uff1a<\/p>\n\n\n\n

          \n
        1. CDS Hooks\uff1a\u6b64\u9879\u76ee\u4e3aFHIR\uff08Fast Healthcare Interoperability Resources\uff09\u7684\u4e00\u90e8\u5206\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e00\u79cd\u673a\u5236\uff0c\u53ef\u4ee5\u5c06\u5916\u90e8\u51b3\u7b56\u652f\u6301\u7cfb\u7edf\u96c6\u6210\u5230\u4e34\u5e8a\u4fe1\u606f\u7cfb\u7edf\u4e2d\u3002<\/li>\n\n\n\n
        2. OHDSI\uff08Observational Health Data Sciences and Informatics\uff09\uff1a\u8fd9\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u4e34\u5e8a\u6570\u636e\u7814\u7a76\u7f51\u7edc\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u5de5\u5177\u548c\u65b9\u6cd5\uff0c\u5e2e\u52a9\u7814\u7a76\u4eba\u5458\u8fdb\u884c\u4e34\u5e8a\u51b3\u7b56\u652f\u6301\u548c\u4e34\u5e8a\u7814\u7a76\u3002<\/li>\n\n\n\n
        3. Prodigy\uff1a\u8fd9\u662f\u4e00\u4e2aPython\u5e93\uff0c\u7528\u4e8e\u5728\u4e34\u5e8a\u73af\u5883\u4e2d\u5feb\u901f\u5f00\u53d1\u4e34\u5e8a\u51b3\u7b56\u652f\u6301\u7cfb\u7edf\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e9b\u5e38\u89c1\u7684\u673a\u5668\u5b66\u4e60\u548c\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7b97\u6cd5\uff0c\u53ef\u7528\u4e8e\u5206\u6790\u4e34\u5e8a\u6570\u636e\u548c\u751f\u6210\u51b3\u7b56\u652f\u6301\u5efa\u8bae\u3002<\/li>\n\n\n\n
        4. clinicaltrialsgov-api\uff1a\u8fd9\u662f\u4e00\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u63d0\u4f9b\u4e86\u5bf9\u4e34\u5e8a\u8bd5\u9a8c\u6570\u636e\u5e93clinicaltrials.gov\u7684API\u8bbf\u95ee\u3002\u901a\u8fc7\u4f7f\u7528\u8fd9\u4e2aAPI\uff0c\u5f00\u53d1\u4eba\u5458\u53ef\u4ee5\u8bbf\u95ee\u548c\u68c0\u7d22clinicaltrials.gov\u4e0a\u7684\u4e34\u5e8a\u8bd5\u9a8c\u6570\u636e\uff0c\u4ee5\u652f\u6301\u4e34\u5e8a\u51b3\u7b56\u3002<\/li>\n<\/ol>\n\n\n\n

          \u8bf7\u6ce8\u610f\uff0c\u8fd9\u53ea\u662f\u4e00\u4e9b\u5728GitHub\u4e0a\u53ef\u7528\u7684\u4e34\u5e8a\u51b3\u7b56\u652f\u6301\u7684\u5f00\u6e90\u9879\u76ee\u7684\u4f8b\u5b50\uff0c\u8fd8\u6709\u8bb8\u591a\u5176\u4ed6\u9879\u76ee\u4e5f\u53ef\u4ee5\u7528\u4e8e\u6b64\u76ee\u7684\u3002<\/p>\n\n\n\n

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

          \u5728GitHub\u4e0a\u6709\u8bb8\u591a\u57fa\u56e0\u7ec4\u5b66\u7684\u5f00\u6e90\u9879\u76ee\u3002\u4ee5\u4e0b\u662f\u5176\u4e2d\u4e00\u4e9b\u9879\u76ee\u7684\u4f8b\u5b50\uff1a<\/p>\n\n\n\n

            \n
          1. Bioconductor\uff1a\u7528\u4e8e\u751f\u7269\u5b66\u548c\u57fa\u56e0\u7ec4\u5b66\u5206\u6790\u7684\u5f00\u6e90\u8f6f\u4ef6\u5e73\u53f0\u3002<\/li>\n\n\n\n
          2. GATK (Genome Analysis Toolkit)\uff1a\u7528\u4e8e\u57fa\u56e0\u7ec4\u5206\u6790\u7684\u5e7f\u6cdb\u4f7f\u7528\u7684\u5f00\u6e90\u5de5\u5177\u5305\u3002<\/li>\n\n\n\n
          3. BEDTools\uff1a\u7528\u4e8e\u57fa\u56e0\u7ec4\u6ce8\u91ca\u548c\u533a\u57df\u5206\u6790\u7684\u5f00\u6e90\u547d\u4ee4\u884c\u5de5\u5177\u96c6\u3002<\/li>\n\n\n\n
          4. Samtools\uff1a\u7528\u4e8e\u5904\u7406SAM\/BAM\u6587\u4ef6\u548c\u8fdb\u884c\u57fa\u56e0\u7ec4\u5e8f\u5217\u5206\u6790\u7684\u5f00\u6e90\u5de5\u5177\u3002<\/li>\n\n\n\n
          5. BWA (Burrows Wheeler Aligner)\uff1a\u7528\u4e8e\u57fa\u56e0\u7ec4\u6bd4\u5bf9\u548c\u5e8f\u5217\u6bd4\u5bf9\u7684\u5f00\u6e90\u8f6f\u4ef6\u3002<\/li>\n\n\n\n
          6. Ensembl\uff1a\u63d0\u4f9b\u57fa\u56e0\u7ec4\u6ce8\u91ca\u548c\u57fa\u56e0\u7ec4\u6570\u636e\u7684\u5f00\u6e90\u6570\u636e\u5e93\u548c\u8f6f\u4ef6\u3002<\/li>\n\n\n\n
          7. Galaxy\uff1a\u7528\u4e8e\u751f\u7269\u5b66\u6570\u636e\u5206\u6790\u7684\u5f00\u6e90\u3001\u57fa\u4e8e\u7f51\u7edc\u7684\u5de5\u4f5c\u6d41\u7a0b\u7ba1\u7406\u7cfb\u7edf\u3002<\/li>\n\n\n\n
          8. Snakemake\uff1a\u7528\u4e8e\u6784\u5efa\u548c\u6267\u884c\u57fa\u56e0\u7ec4\u5b66\u5206\u6790\u5de5\u4f5c\u6d41\u7a0b\u7684\u5f00\u6e90\u5de5\u5177\u3002<\/li>\n\n\n\n
          9. DeepVariant\uff1a\u8c37\u6b4c\u5f00\u53d1\u7684\u7528\u4e8e\u57fa\u56e0\u7ec4\u53d8\u5f02\u68c0\u6d4b\u7684\u5f00\u6e90\u8f6f\u4ef6\u3002<\/li>\n\n\n\n
          10. SnpEff\uff1a\u7528\u4e8e\u57fa\u56e0\u7ec4\u6ce8\u91ca\u548c\u53d8\u5f02\u6548\u679c\u9884\u6d4b\u7684\u5f00\u6e90\u5de5\u5177\u3002<\/li>\n<\/ol>\n\n\n\n

            \u8fd9\u53ea\u662f\u4e00\u5c0f\u90e8\u5206\u5728GitHub\u4e0a\u53ef\u7528\u7684\u57fa\u56e0\u7ec4\u5b66\u5f00\u6e90\u9879\u76ee\uff0c\u8fd8\u6709\u8bb8\u591a\u5176\u4ed6\u9879\u76ee\u4e5f\u5728\u4e0d\u65ad\u5f00\u53d1\u548c\u66f4\u65b0\u4e2d\u3002<\/p>\n\n\n\n

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

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

            \u4ee5\u4e0b\u662f\u4e00\u4e9b GitHub \u4e0a\u7684\u5065\u5eb7\u7ba1\u7406\u5f00\u6e90\u9879\u76ee\uff1a<\/p>\n\n\n\n

              \n
            1. OpenMRS\uff1a\u4e00\u4e2a\u7528\u4e8e\u7ba1\u7406\u548c\u8ddf\u8e2a\u75c5\u4eba\u5065\u5eb7\u4fe1\u606f\u7684\u5168\u7403\u5f00\u6e90\u533b\u7597\u8f6f\u4ef6\u3002
              GitHub \u94fe\u63a5\uff1ahttps:\/\/github.com\/openmrs\/openmrs-core<\/li>\n\n\n\n
            2. FHIR\uff1aHealth Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) \u6807\u51c6\u7684\u5b98\u65b9\u5b9e\u73b0\u3002
              GitHub \u94fe\u63a5\uff1ahttps:\/\/github.com\/HL7<\/li>\n\n\n\n
            3. openEHR\uff1a\u4e00\u4e2a\u5f00\u653e\u7684\u7535\u5b50\u5065\u5eb7\u8bb0\u5f55\u89c4\u8303\u548c\u6280\u672f\u6846\u67b6\uff0c\u65e8\u5728\u63d0\u4f9b\u4e34\u5e8a\u548c\u7ba1\u7406\u6570\u636e\u7684\u53ef\u4e92\u64cd\u4f5c\u6027\u3002
              GitHub \u94fe\u63a5\uff1ahttps:\/\/github.com\/openEHR<\/li>\n\n\n\n
            4. OpenEMR\uff1a\u4e00\u4e2a\u5f00\u6e90\u7684\u7535\u5b50\u533b\u7597\u8bb0\u5f55 (EMR) \u548c\u533b\u7597\u5b9e\u8df5\u7ba1\u7406\u7cfb\u7edf (PM)\u3002
              GitHub \u94fe\u63a5\uff1ahttps:\/\/github.com\/openemr\/openemr<\/li>\n\n\n\n
            5. HAPI-FHIR\uff1a\u4e00\u4e2a\u7528\u4e8e Java \u7684\u5f00\u6e90 FHIR \u5e93\uff0c\u7528\u4e8e\u521b\u5efa\u3001\u89e3\u6790\u548c\u64cd\u4f5c FHIR \u8d44\u6e90\u3002
              GitHub \u94fe\u63a5\uff1ahttps:\/\/github.com\/jamesagnew\/hapi-fhir<\/li>\n<\/ol>\n\n\n\n

              \u8fd9\u4e9b\u9879\u76ee\u63d0\u4f9b\u4e86\u5065\u5eb7\u7ba1\u7406\u9886\u57df\u7684\u8bb8\u591a\u4e0d\u540c\u65b9\u9762\u7684\u529f\u80fd\u548c\u89e3\u51b3\u65b9\u6848\uff0c\u5305\u62ec\u7535\u5b50\u533b\u7597\u8bb0\u5f55\u3001\u5065\u5eb7\u6570\u636e\u4e92\u64cd\u4f5c\u6027\u3001\u533b\u7597\u5b9e\u8df5\u7ba1\u7406\u7b49\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

              \u5728GitHub\u4e0a\uff0c\u6709\u8bb8\u591a\u4eba\u5de5\u667a\u80fd\u6280\u672f\u5728\u533b\u7597\u884c\u4e1a\u7684\u5e94\u7528\u9879\u76ee\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u9879\u76ee\u793a\u4f8b\uff1a \u8fd9\u4e9b\u9879\u76ee\u63d0\u4f9b\u4e86\u4e0d\u540c\u65b9\u9762\u7684 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,14],"tags":[],"class_list":["post-157","post","type-post","status-publish","format-standard","hentry","category-7","category-med"],"blocksy_meta":"","_links":{"self":[{"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/posts\/157","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/comments?post=157"}],"version-history":[{"count":2,"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/posts\/157\/revisions"}],"predecessor-version":[{"id":160,"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/posts\/157\/revisions\/160"}],"wp:attachment":[{"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/media?parent=157"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/categories?post=157"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/ai.gitpp.com\/index.php\/wp-json\/wp\/v2\/tags?post=157"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}