Machine learning models deployed in healthcare systems face data drawn from continually evolving environments. However, researchers proposing such models typically evaluate them in a time-agnostic manner, with train and test splits sampling patients throughout the entire study period. We introduce the Evaluation on Medical Datasets Over Time (EMDOT) framework and Python package, which evaluates the performance of a model class over time. Across five medical datasets and a variety of models, we compare two training strategies: (1) using all historical data, and (2) using a window of the most recent data. We note changes in performance over time, and identify possible explanations for these shocks.

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This article describes one person's experience in coming from an academic environment to work at Digital Equipment Corpo I've divided this history into two distinct parts. AI and DEC's entry into the AI market, DEC engineers were This article is an edited version of Dr Polit's presentation at the Technology Transfer Symposium held at the AAAI-83 conference Building Expert Systems I'll now give a brief review of the steps involved in building expert systems as they are described by many researchers. The five steps involved in building an expert system are: Step 1: problem recognition, Step 2: task definition, Step 3: initial design, Step 4: knowledge acquisition, and Step 5: system maintenance. Frequently, the problem is perceived as a bottleneck in a larger process; sometimes it is a scarcity of traiued personnel. Second, during step 2, researchers must define the functions the AI system will perform.

A Broadened Perspective of Manufacturing: The Knowledge Network In order to form a vision and a strategy, we took a broad new look at our manufacturing business. The perspective ranged from the customer at the point of sale through point of manufacture and point of distribution and back to the customer. In 1981 DEC coined the term knowledge network to represent this notion (O'Connor 1984) (see figure 1). In many of these "pockets of expertise, " within DEC or any other manufacturing business, the expertise and the reasons for making decisions are generally undocumented or are unavailable to all the parties needing the information. Two Views of the Business Within the knowledge network two major cycles are apparent: the order-process cycle and the product life cycle The order-process cycle (see figure 2) is oriented around taking, manufacturing, delivering, and servicing an order.