{"id":44428,"date":"2023-08-09T19:59:06","date_gmt":"2023-08-09T11:59:06","guid":{"rendered":"https:\/\/swarma.org\/?p=44428"},"modified":"2023-08-09T19:59:06","modified_gmt":"2023-08-09T11:59:06","slug":"nat-mach-intell-%e9%80%9f%e9%80%92%ef%bc%9a%e4%b8%b4%e5%ba%8a%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e7%9a%84%e7%ae%97%e6%b3%95%e5%85%ac%e5%b9%b3%e6%80%a7%e5%92%8c%e5%87%8f%e5%b0%91%e5%81%8f%e5%b7%ae","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=44428","title":{"rendered":"Nat. Mach. Intell. \u901f\u9012\uff1a\u4e34\u5e8a\u673a\u5668\u5b66\u4e60\u7684\u7b97\u6cd5\u516c\u5e73\u6027\u548c\u51cf\u5c11\u504f\u5dee"},"content":{"rendered":"
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\u8bba\u6587\u9898\u76ee\uff1aAlgorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning<\/span><\/section>\n

\u671f\u520a\u540d\u79f0\uff1aNature Machine Intelligence<\/em><\/span><\/p>\n

\u6591\u56fe\u5730\u5740\uff1ahttps:\/\/pattern.swarma.org\/paper\/b9bffc4a-2ff7-11ee-a742-0242ac17000d<\/span><\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/www.nature.com\/articles\/s42256-023-00697-3<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/blockquote>\n


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\u968f\u7740\u57fa\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u6a21\u578b\u4e0d\u65ad\u5f00\u53d1\u7528\u4e8e\u533b\u7597\u5e94\u7528\u9886\u57df\uff0c\u9700\u8981\u66f4\u5927\u7684\u52aa\u529b\u6765\u786e\u4fdd\u8fd9\u4e9b\u6280\u672f\u4e0d\u4f1a\u53cd\u6620\u6216\u52a0\u5267\u6570\u636e\u4e2d\u53ef\u80fd\u5b58\u5728\u7684\u4e0d\u826f\u6216\u6b67\u89c6\u6027\u504f\u89c1\u3002<\/span><\/p>\n


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\u8fd9\u9879\u53d1\u8868\u4e8e Nature Machine Intelligence<\/em> \u7684\u6700\u65b0\u7814\u7a76\u5f15\u5165\u4e86\u4e00\u4e2a\u5f3a\u5316\u5b66\u4e60\u6846\u67b6\uff0c\u80fd\u591f\u51cf\u8f7b\u6570\u636e\u6536\u96c6\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u4ea7\u751f\u7684\u504f\u89c1\u3002\u5177\u4f53\u800c\u8a00\uff0c\u5bf9\u4e8e\u8fc5\u901f\u9884\u6d4b\u524d\u5f80\u533b\u9662\u6025\u8bca\u79d1\u7684\u60a3\u8005\u662f\u5426\u611f\u67d3 COVID-19 \u7684\u4efb\u52a1\uff0c\u7814\u7a76\u8005\u5bf9\u6a21\u578b\u505a\u4e86\u8bc4\u4f30\uff0c\u65e8\u5728\u51cf\u8f7b\u6570\u636e\u4e2d\u5b58\u5728\u7684\u57fa\u4e8e\u533b\u9662\u548c\u79cd\u65cf\u7684\u504f\u89c1\u3002<\/span><\/p>\n


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\u56fe2. \u5355\u6d41\u548c\u5bf9\u6297 Q \u7f51\u7edc\u7684\u6bd4\u8f83\u3002<\/span><\/p>\n


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\u56fe3. t-SNE \u8868\u5f81\u3002\u901a\u8fc7 t-SNE \u786e\u5b9a\u7684\u805a\u7c7b\u53ef\u89c6\u5316\uff0c\u5305\u542b\u6240\u6709 COVID-19 \u75c5\u4f8b\u3002<\/span><\/p>\n


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\u5927\u6a21\u578b\u4e0e\u751f\u547d\u533b\u5b66\uff1a<\/strong><\/p>\n

AI + Science\u7b2c\u4e8c\u5b63\u8bfb\u4e66\u4f1a\u542f\u52a8<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


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\u5927\u6a21\u578b\u4e0e\u751f\u7269\u533b\u5b66\uff1aAI + Science\u7b2c\u4e8c\u5b63\u8bfb\u4e66\u4f1a\u542f\u52a8<\/a><\/span>
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\u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n

\u200d<\/span>1. <\/strong>Nature \u901f\u9012\uff1a\u5927\u8bed\u8a00\u6a21\u578b\u7f16\u7801\u4e34\u5e8a\u77e5\u8bc6<\/a><\/strong><\/span><\/strong><\/strong><\/section>\n
2.<\/strong> Nature \u901f\u9012\uff1a\u5927\u6a21\u578b\u8bad\u7ec3\u533b\u5b66\u5168\u624d AI<\/a><\/strong><\/span><\/strong><\/section>\n
3. <\/strong><\/strong>\u56e0\u679c\u63a8\u65ad\u5728\u533b\u836f\u56fe\u50cf\u7684\u5e94\u7528\uff1a\u6570\u636e\u7f3a\u5931\u548c\u6570\u636e\u4e0d\u5339\u914d<\/a><\/strong><\/strong><\/span><\/strong><\/strong><\/section>\n
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4. <\/strong><\/strong><\/span>\u5f20\u6c5f\uff1a\u7b2c\u4e09\u4ee3\u4eba\u5de5\u667a\u80fd\u6280\u672f\u57fa\u7840\u2014\u2014\u4ece\u53ef\u5fae\u5206\u7f16\u7a0b\u5230\u56e0\u679c\u63a8\u7406 | \u96c6\u667a\u5b66\u56ed\u5168\u65b0\u8bfe\u7a0b<\/a><\/strong><\/strong><\/span><\/section>\n
5. <\/strong><\/strong>\u52a0\u5165\u96c6\u667a\u5b66\u56edVIP\uff0c\u83b7\u5f9720\u5468\u5e74\u201c\u6d8c\u73b0\u201d\u5b66\u672f\u5e74\u4f1a\u5165\u573a\u5238\uff01<\/a><\/strong><\/strong><\/strong><\/strong><\/span><\/section>\n
6. <\/strong>\u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/strong><\/span><\/a><\/section>\n

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\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u8bfb\u4e66\u4f1a<\/strong><\/strong><\/span><\/strong><\/section>\n

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\u5173\u952e\u8bcd\uff1a\u673a\u5668\u5b66\u4e60\uff0c\u5f3a\u5316\u5b66\u4e60\uff0c\u7b97\u6cd5\u516c\u5e73\u6027\uff0c\u6570\u636e\u504f\u5dee\uff0c\u6a21\u578b\u6cdb\u5316\u80fd\u529b \u8bba\u6587\u9898\u76ee\uff1aAlgorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning \u671f\u520a\u540d\u79f0\uff1aNatu…<\/p>\n","protected":false},"author":0,"featured_media":44422,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"special":[],"_links":{"self":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/44428"}],"collection":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=44428"}],"version-history":[{"count":0,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/44428\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/media\/44422"}],"wp:attachment":[{"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=44428"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=44428"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=44428"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fspecial&post=44428"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}