1,331 research outputs found
Expert-Augmented Machine Learning
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
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
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 18â88 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
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
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
Impact of a National Collaborative Care Initiative for Patients with Depression, Diabetes and Heart Disease
'We could be rich':Unemployment, roadblocks and the rhythms of hydrocarbon work among the GuaranĂ of the Argentine Chaco
Developing autonomous learning in first year university students using perspectives from positive psychology
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 firstâyear 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 psychoâeducational intervention designed to increase their selfâefficacy and selfâesteem. 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 selfâefficacy, selfâesteem and autonomous learning in ways that were theoretically meaningful
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