<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI | Scott Miner</title><link>https://scottminer.rbind.io/tags/ai/</link><atom:link href="https://scottminer.rbind.io/tags/ai/index.xml" rel="self" type="application/rss+xml"/><description>AI</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 19 Jun 2023 00:00:00 +0000</lastBuildDate><image><url>https://scottminer.rbind.io/media/sharing.png</url><title>AI</title><link>https://scottminer.rbind.io/tags/ai/</link></image><item><title>Healthcare Expert System</title><link>https://scottminer.rbind.io/projects/healthcare-expert-system/</link><pubDate>Mon, 19 Jun 2023 00:00:00 +0000</pubDate><guid>https://scottminer.rbind.io/projects/healthcare-expert-system/</guid><description>&lt;p&gt;A rule-based expert system that models the decision logic used in heart failure telemonitoring. Given patient-reported measurements and symptoms, the system applies clinical rules to suggest self-care actions and flag situations that need a clinician&amp;rsquo;s attention.&lt;/p&gt;
&lt;h2 id="how-it-works"&gt;How it works&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Domain knowledge is encoded as &lt;strong&gt;rules&lt;/strong&gt; in Pyke, a Python knowledge engine.&lt;/li&gt;
&lt;li&gt;Patient facts (weight changes, blood pressure, symptoms) are asserted into the knowledge base.&lt;/li&gt;
&lt;li&gt;The inference engine fires matching rules to produce recommendations and alerts.&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="what-it-demonstrates"&gt;What it demonstrates&lt;/h2&gt;
&lt;p&gt;Symbolic AI and knowledge representation as a complement to statistical machine learning, and translating a real clinical workflow into explicit, auditable rules.&lt;/p&gt;</description></item></channel></rss>