1,331 research outputs found

    Expert-Augmented Machine Learning

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    Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

    Photometric Variability in the Ultracool Dwarf BRI 0021-0214: Possible Evidence for Dust Clouds

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    We report CCD photometric monitoring of the nonemission ultracool dwarf BRI 0021-0214 (M9.5) obtained during 10 nights in 1995 November and 4 nights in 1996 August, with CCD cameras at 1 m class telescopes on the observatories of the Canary Islands. We present differential photometry of BRI 0021-0214, and we report significant variability in the I-band light curve obtained in 1995. A periodogram analysis finds a strong peak at a period of 0.84 day. This modulation appears to be transient because it is present in the 1995 data but not in the 1996 data. We also find a possible period of 0.20 day, which appears to be present in both the 1995 and 1996 datasets. However, we do not find any periodicity close to the rotation period expected from the spectroscopic rotational broadening (< 0.14 day). BRI 0021-0214 is a very inactive object, with extremely low levels of Halpha and X-ray emission. Thus, it is unlikely that magnetically induced cool spots can account for the photometric variability. The photometric variability of BRI 0021-0214 could be explained by the presence of an active meteorology that leads to inhomogeneous clouds on the surface. The lack of photometric modulation at the expected rotational period suggests that the pattern of surface features may be more complicated than previously anticipated.Comment: Accepted for publication in ApJ. 26 pages, 13 figures include

    The Effects of Patient-Centered Depression Care on Patient Satisfaction and Depression Remission

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    Background: While health systems are striving for patient-centered care, they have little evidence to guide them on how to engage patients in their care, or how this may affect patient experiences and outcomes. Objective: To explore which specific patient-centered aspects of care were best associated with depression improvement and care satisfaction. Methods: Design - observational. Setting - 83 primary care clinics across Minnesota. Subjects - Primary care patients with new prescriptions for antidepressants for depression were recruited from 2007 to 2009. Outcome measures - Patients completed phone surveys regarding demographics and self-rated health status and depression severity at baseline and 6 months. Patient centeredness was assessed via a modified version of the Patient Assessment of Chronic Illness Care. Differences in rates of remission and satisfaction between positive and negative responses for each care process were evaluated using chi-square tests. Results: At 6 months, 37% of 792 patients ages 18–88 achieved depression remission, and 79% rated their care as good-to-excellent. Soliciting patient preferences for care and questions or concerns, providing treatment plans, utilizing depression scales and asking about suicide risk were patient centered measures that were positively associated with depression remission in the unadjusted model; these associations were mildly weakened after adjustment for depression severity and health status. Nearly all measures of patient centeredness were positively associated with care ratings. Conclusion: The patient centeredness of care influences how patients experience and rate their care. This study identified specific actions providers can take to improve patient satisfaction and depression outcomes

    Support varieties for selfinjective algebras

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    Support varieties for any finite dimensional algebra over a field were introduced by Snashall-Solberg using graded subalgebras of the Hochschild cohomology. We mainly study these varieties for selfinjective algebras under appropriate finite generation hypotheses. Then many of the standard results from the theory of support varieties for finite groups generalize to this situation. In particular, the complexity of the module equals the dimension of its corresponding variety, all closed homogeneous varieties occur as the variety of some module, the variety of an indecomposable module is connected, periodic modules are lines and for symmetric algebras a generalization of Webb's theorem is true

    Clinician Burnout and Satisfaction with Resources in Caring for Complex Patients

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    Objective: To describe primary care clinicians\u27 self-reported satisfaction, burnout and barriers for treating complex patients. Methods: We conducted a survey of 1554 primary care clinicians in 172 primary care clinics in 18 health care systems across 8 states prior to the implementation of a collaborative model of care for patients with depression and diabetes and/or cardiovascular disease. Results: Of the clinicians who responded to the survey (n=709; 46%), we found that a substantial minority (31%) were experiencing burnout that was associated with lower career satisfaction (P\u3c.0001) and lower satisfaction with resources to treat complex patients (P\u3c.0001). Less than 50% of clinicians rated their ability to treat complex patients as very good to excellent with 21% rating their ability as fair to poor. The majority of clinicians (72%) thought that a collaborative model of care would be very helpful for treating complex patients. Conclusions: Burnout remains a problem for primary care clinicians and is associated with low job satisfaction and low satisfaction with resources to treat complex patients. A collaborative care model for patients with mental and physical health problems may provide the resources needed to improve the quality of care for these patients

    Developing autonomous learning in first year university students using perspectives from positive psychology

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    Autonomous learning is a commonly occurring learning outcome from university study, and it is argued that students require confidence in their own abilities to achieve this. Using approaches from positive psychology, this study aimed to develop confidence in first‐year university students to facilitate autonomous learning. Psychological character strengths were assessed in 214 students on day one at university. Two weeks later their top three strengths were given to them in study skills modules as part of a psycho‐educational intervention designed to increase their self‐efficacy and self‐esteem. The impact of the intervention was assessed against a control group of 40 students who had not received the intervention. The results suggested that students were more confident after the intervention, and that levels of autonomous learning increased significantly compared to the controls. Character strengths were found to be associated with self‐efficacy, self‐esteem and autonomous learning in ways that were theoretically meaningful
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