We propose the Multimodal Clinical Benchmark for Emergency Care (MC-BEC), a comprehensive benchmark for evaluating foundation models in Emergency Medicine using a dataset of 100K+ continuously monitored Emergency Department visits from 2020-2022. MC-BEC focuses on clinically relevant prediction tasks at timescales from minutes to days, including predicting patient decompensation, disposition, and emergency department (ED) revisit, and includes a standardized evaluation framework with train-test splits and evaluation metrics. The multimodal dataset includes a wide range of detailed clinical data, including triage information, prior diagnoses and medications, continuously measured vital signs, electrocardiogram and photoplethysmograph waveforms, orders placed and medications administered throughout the visit, free-text reports of imaging studies, and information on ED diagnosis, disposition, and subsequent revisits. We provide performance baselines for each prediction task to enable the evaluation of multimodal, multitask models. We believe that MC-BEC will encourage researchers to develop more effective, generalizable, and accessible foundation models for multimodal clinical data.

According to usability experts, the top user issue for Web sites is difficult navigation. We have been developing auto-mated usability tools for several years, and here we describe a prototype service called InfoScent™ Bloodhound Simula-tor, a push-button navigation analysis system, which auto-matically analyzes the information cues on a Web site to produce a usability report. We further build upon previous algorithms to create a method called Information Scent Absorption Rate, which measures the navigability of a site by computing the probability of users reaching the desired destinations on the site. Lastly, we present a user study involving 244 subjects over 1385 user sessions that show how Bloodhound correlates with real users surfing for in-formation on four Web sites. The hope is that, by using a simulation of user surfing behavior, we can reduce the need for human labor during usability testing, thus dramatically lower testing costs, and ultimately improving user experience. The Bloodhound Project is unique in that we apply a concrete HCI theory directly to a real-world prob-lem. The lack of empirically validated HCI theoretical model has plagued the development of our field, and this is a step toward that direction.

Despite their potential benefits, statistical design/optimization techniques are often not routinely used by industry because of prohibitive costs and/or lack of generality. To overcome these obstacles, we present a general approach to statistical design which is computationally inexpensive and applicable to an extensive spectrum of analog-digital circuits, unlike previous inexpensive methods which limit the user to specific technologies, standard device models, and/or purely digital designs. This general applicability and cost efficiency is maintained through four factors. First, an efficient screening algorithm minimizes the dimensionality of the input parameter space by identifying the important input parameters. Second, a general, accurate, parsimonious nonparametric regression model is formulated so that a wide range of behavior between input parameters and output performances can be mapped, not just those with a linear regression relationship. Third, this approach tightly couples with a compiler-methodology based simulator which sustains the achieved flexibility through its model independence. Finally, a waveform analysis capability completely automates the procedure. An industry ECL bandgap regulator circuit illustrates the benefits of this method.>

Despite their indisputable benefits, parametric yield prediction/optimization techniques are often not routinely used by industry because of prohibitive costs and/or lack of generality. To overcome these obstacles, we present a new statistical technology independent parametric yield approach which is computationally inexpensive and generally applicable, unlike previous inexpensive methods which limit the user to specific technologies, device models, or circuits. This general applicability and cost efficiency is maintained through four factors. First, this approach interfaces with a compiler-methodology based simulator which establishes complete model independence. Second, critical parameters are not predetermined; an efficient screening procedure minimizes the dimensionality of the input parameter space so as to formulate a parsimonious nonparametric regression model. Third, because of the flexibility of this nonparametric model, the capability exists to map any input parameters to an output performance, not just those with a linear relationship. Finally, a waveform analysis capability completely automates the approach, thereby enabling turn-key operation. An ECL bandgap regulator circuit illustrates the benefits of this approach.