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	<title>temporal cross-validation &#8211; BIOENGINEER.ORG</title>
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		<title>Synthetic Japanese claims benchmark puts healthcare fraud detection to a frozen, one-shot test</title>
		<link>https://bioengineer.org/synthetic-japanese-claims-benchmark-puts-healthcare-fraud-detection-to-a-frozen-one-shot-test/</link>
		
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		<pubDate>Mon, 26 Oct 2026 19:42:55 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[data leakage]]></category>
		<category><![CDATA[fraud detection]]></category>
		<category><![CDATA[healthcare fraud]]></category>
		<category><![CDATA[Japan]]></category>
		<category><![CDATA[LightGBM]]></category>
		<category><![CDATA[machine learning benchmark]]></category>
		<category><![CDATA[medical claims]]></category>
		<category><![CDATA[model calibration]]></category>
		<category><![CDATA[provider de-linking]]></category>
		<category><![CDATA[Reproducibility]]></category>
		<category><![CDATA[synthetic health data]]></category>
		<category><![CDATA[temporal cross-validation]]></category>
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					<description><![CDATA[Researchers built a synthetic, Japan-calibrated medical claims benchmark with traceable fraud counterfactuals and a frozen single-access evaluation, reporting strong anti-fraud machine learning performance while cautioning it establishes no real-world validity.]]></description>
		
		
		
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