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- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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- 2017
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In: Physical Review D. - 2470-0010 .- 2470-0029. ; 96:2
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Journal article (peer-reviewed)
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- Belov, Vladimir, et al.
(author)
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Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
- 2024
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In: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
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Journal article (peer-reviewed)abstract
- Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.
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- Crowe, S., et al.
(author)
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Near-infrared observations of outflows and young stellar objects in the massive star-forming region AFGL 5180
- 2024
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In: Astronomy and Astrophysics. - 0004-6361 .- 1432-0746. ; 682
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Journal article (peer-reviewed)abstract
- Context. Massive stars play important roles throughout the universe; however, their formation remains poorly understood. Observations of jets and outflows in high-mass star-forming regions, as well as surveys of young stellar object (YSO) content, can help test theoretical models of massive star formation. Aims. We aim at characterizing the massive star-forming region AFGL 5180 in the near-infrared (NIR), identifying outflows and relating these to sub-mm/mm sources, as well as surveying the overall YSO surface number density to compare to massive star formation models. Methods. Broad- and narrow-band imaging of AFGL 5180 was made in the NIR with the Large Binocular Telescope, in both seeing-limited (~0.5′) and high angular resolution (~0.09′) Adaptive Optics (AO) modes, as well as with the Hubble Space Telescope. Archival continuum data from the Atacama Millimeter/Submillimeter Array (ALMA) was also utilized. Results. At least 40 jet knots were identified via NIR emission from H2 and [FeII] tracing shocked gas. Bright jet knots outflowing from the central most massive protostar, S4 (estimated mass ~11 M⊙, via SED fitting), are detected towards the east of the source and are resolved in fine detail with the AO imaging. Additional knots are distributed throughout the field, likely indicating the presence of multiple driving sources. Sub-millimeter sources detected by ALMA are shown to be grouped in two main complexes, AFGL 5180 M and a small cluster ~15′ (0.15 pc in projection) to the south, AFGL 5180 S. From our NIR continuum images we identify YSO candidates down to masses of ~0.1 M⊙. Combined with the sub-mm sources, this yields a surface number density of such YSOs of N* ~ 103pc-2 within a projected radius of about 0.1 pc. Such a value is similar to those predicted by models of both core accretion from a turbulent clump environment and competitive accretion. The radial profile of N* is relatively flat on scales out to 0.2 pc, with only modest enhancement around the massive protostar inside 0.05 pc, which provides additional constraints on these massive star formation models. Conclusions. This study demonstrates the utility of high-resolution NIR imaging, in particular with AO, for detecting outflow activity and YSOs in distant regions. The presented images reveal the complex morphology of outflow-shocked gas within the large-scale bipolar flow of a massive protostar, as well as clear evidence for several other outflow driving sources in the region. Finally, this work presents a novel approach to compare the observed YSO surface number density from our study against different models of massive star formation.
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- Gunnarsdottir, Gudrun M., et al.
(author)
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Validation of the Hospital Frailty Risk Score in older surgical patients : A population-based retrospective cohort study
- 2021
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In: Acta Anaesthesiologica Scandinavica. - : John Wiley & Sons. - 0001-5172 .- 1399-6576. ; 65:8, s. 1033-1042
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Journal article (peer-reviewed)abstract
- Background: There is a need for standardized and cost-effective identification of frailty risk. The objective was to validate the Hospital Frailty Risk Score which utilizes International Classification Diagnoses in a cohort of older surgical patients, assess the score as an independent risk factor for adverse outcomes and compare discrimination properties of the frailty risk score with other risk stratification scores.Methods: Data were analysed from all patients >= 65 years undergoing primary surgical procedures from 2006-2018. Patients were categorized based on the frailty risk score. The primary outcomes were 30-day mortality and 180-day risk of readmission.Results: Of 16 793 patients evaluated, 7480 (45%), 7605 (45%) and 1708 (10%) had a low, intermediate and high risk of frailty. There was a higher incidence of 30-day mortality for individuals with intermediate (2.9%) and high (8.3%) compared with low (1.4%) risk of frailty (P < .001 for both comparisons). Similarly, the hazard of readmission within the first 180 days was higher for intermediate (HR 1.25; 95% CI: 1.16-1.34) and high (HR 1.84; 95% CI: 1.66-2.03) compared with low (HR 1.00, P < .001 for both comparisons) risk of frailty. The hazard of long-term mortality was higher for intermediate (HR 1.70; 95% CI: 1.61-1.80) and high (HR 4.16; 95% CI: 3.84-4.49) compared with low (HR 1.00, P < .001 for both comparisons) risk of frailty. Finally, long length of primary hospitalization occurred for 9.3%, 15.0% and 27.3% of individuals with low, intermediate and high frailty risk (P < .001 for all comparisons). A model including age and ASA classification had the best discrimination for 30-day mortality (AUC 0.862; 95% CI: 0.847-0.877).Conclusion: Our findings suggest that the Hospital Frailty Risk Score might be used to screen older surgical patients for risk of frailty. While only slightly improving prediction of 30-day mortality using the ASA classification, the Hospital Frailty Risk Score can be used to independently classify older patients for the risk of important outcomes using pre-existing readily available electronic data.
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