8 research outputs found

    DEVELOPMENT, VALIDATION, AND IMPLEMENTATION OF A MAINSTREAMING PROCESS TO TRANSITION STUDENTS FROM SELF-CONTAINED SPECIAL EDUCATION INTO GENERAL EDUCATION PLACEMENTS

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    We developed a set of computational tools specifically to guide qualified special education students back into general education. These tools include a decision tree to identify candidate students and elucidate successful placement in general education. Candidate students enter a process involving selection of general education classroom, data collection, and finally how to make the final transition out of special education self-contained placements. In the 2015-2016, we undertook a limited implementation of these transenvironmental programming tools and facilitated the transition of 10 of 20 identified candidate students from self-contained academic special education classrooms into general education placements. In the 2016-2017 school year, we extended this process to include 4 schools. 16 of 53 identified candidate students from self-contained academic special education classrooms were able to transition into general education placements. In an extension of the model district-wide, 9 of 26 identified students from behavior/SEL unit classrooms, and 9 of 9 identified students from Life Skills/SID unit classrooms were successfully transitioned into a general education with part-time special education placement. A high percentage of the remaining candidates received >50% of their day in general education classrooms and/or were placed in less restrictive self-contained classrooms. Overall, 54% of identified candidate students were able to access a less restrictive environment as defined by IDEIA. Further, computational analyses using regression tree, unbiased hierarchal clustering, and support vector machine methods are presented to demonstrate the robustness of these methods by recapitulating the results using solely data from special education evaluations.  Article visualizations

    Linking Symptom Inventories using Semantic Textual Similarity

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    An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

    Concomitant occurrence of FXTAS and clinically defined sporadic inclusion body myositis: report of two cases

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    This report describes unique presentations of inclusion body myositis (IBM) in two unrelated patients, one male and one female, with genetically and histologically confirmed fragile X-associated tremor/ataxia syndrome (FXTAS). We summarize overlapping symptoms between two disorders, clinical course, and histopathological analyses of the two patients with FXTAS and sporadic IBM, clinically defined per diagnostic criteria of the European Neuromuscular Centre. In case 1, a post-mortem analysis of available brain and muscle tissues is also described. Histopathological features (rimmed vacuoles) consistent with clinically defined IBM were detected in both presented cases. Postmortem testing in case 1 revealed the presence of an FMR1 premutation allele of 60 CGG repeats in both brain and skeletal muscle samples. Case 2 was a premutation carrier with 71 CGG repeats who had a son with FXS. Given that FXTAS is associated with immune-mediated disorders among premutation carriers, it is likely that the pathogeneses of IBM and FXTAS are linked. This is, to our knowledge, the first report of these two conditions presenting together, which expands our understanding of clinical symptoms and unusual presentations in patients with FXTAS. Following detection of a premutation allele of the FMR1 gene, FXTAS patients with severe muscle pain should be assessed for IBM

    The Politics of Legal Writing: Proceedings of a Conference for Legal Research and Writing Program Directors

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    Economics as a 'Tooled' Discipline: Lawrence R. Klein and the Making of Macroeconometric Modeling, 1939-1959

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