scholarly journals Reliability of Family Dogs’ Sleep Structure Scoring Based on Manual and Automated Sleep Stage Identification

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 927 ◽  
Author(s):  
Anna Gergely ◽  
Orsolya Kiss ◽  
Vivien Reicher ◽  
Ivaylo Iotchev ◽  
Enikő Kovács ◽  
...  
Keyword(s):  
Sleep Stage ◽  
Supervised Machine Learning ◽  
Sleep State ◽  
Logistic Regression Models ◽  
Non Invasive ◽  
Visual Scoring ◽  
Original Dataset ◽  
Eeg Data ◽  
Set Up ◽  
The Individual

Non-invasive polysomnography recording on dogs has been claimed to produce data comparable to those for humans regarding sleep macrostructure, EEG spectra and sleep spindles. While functional parallels have been described relating to both affective (e.g., emotion processing) and cognitive (e.g., memory consolidation) domains, methodologically relevant questions about the reliability of sleep stage scoring still need to be addressed. In Study 1, we analyzed the effects of different coders and different numbers of visible EEG channels on the visual scoring of the same polysomnography recordings. The lowest agreement was found between independent coders with different scoring experience using full (3 h-long) recordings of the whole dataset, and the highest agreement within-coder, using only a fraction of the original dataset (randomly selected 100 epochs (i.e., 100 × 20 s long segments)). The identification of drowsiness was found to be the least reliable, while that of non-REM (rapid eye movement, NREM) was the most reliable. Disagreements resulted in no or only moderate differences in macrostructural and spectral variables. Study 2 targeted the task of automated sleep EEG time series classification. Supervised machine learning (ML) models were used to help the manual annotation process by reliably predicting if the dog was sleeping or awake. Logistic regression models (LogREG), gradient boosted trees (GBT) and convolutional neural networks (CNN) were set up and trained for sleep state prediction from already collected and manually annotated EEG data. The evaluation of the individual models suggests that their combination results in the best performance: ~0.9 AUC test scores.

scholarly journals Assessing the sensitivity of EEG-based frequency-tagging as a metric for statistical learning

2021 ◽  
Author(s):  
Danna Pinto ◽  
Anat Prior ◽  
Elana Zion Golumbic
Keyword(s):  
Statistical Learning ◽  
Artificial Language ◽  
Group Level ◽  
Behavioral Measures ◽  
Individual Level ◽  
Non Invasive ◽  
Eeg Data ◽  
Eeg Recordings ◽  
The Individual ◽  
Low Sensitivity

Statistical Learning (SL) is hypothesized to play an important role in language development. However, the behavioral measures typically used to assess SL, particularly at the level of individual participants, are largely indirect and often have low sensitivity. Recently, a neural metric based on frequency-tagging has been proposed as an alternative and more direct measure for studying SL. Here we tested the sensitivity of frequency-tagging measures for studying SL in individual participants in an artificial language paradigm, using non-invasive EEG recordings of neural activity in humans. Importantly, we use carefully constructed controls, in order to address potential acoustic confounds of the frequency-tagging approach. We compared the sensitivity of EEG-based metrics to both explicit and implicit behavioral tests of SL, and the correspondence between these presumed converging operations. Group-level results confirm that frequency-tagging can provide a robust indication of SL for an artificial language, above and beyond potential acoustic confounds. However, this metric had very low sensitivity at the level of individual participants, with significant effects found only in 30% of participants. Conversely, the implicit behavior measures indicated that SL has occurred in 70% of participants, which is more consistent with the proposed ubiquitous nature of SL. Moreover, there was low correspondence between the different measures used to assess SL. Taken together, while some researchers may find the frequency-tagging approach suitable for their needs, our results highlight the methodological challenges of assessing SL at the individual level, and the potential confounds that should be taken into account when interpreting frequency-tagged EEG data.

Patient Scheduling — (Bibliography)

1977 ◽  
Vol 16 (02) ◽  
pp. 112-115 ◽  
Author(s):  
C. O. Köhler ◽  
G. Wagner ◽  
U. Wolber
Keyword(s):  
Information Processing ◽  
Medical Care ◽  
Medical Informatics ◽  
Relevant Literature ◽  
Patient Scheduling ◽  
Individual Scientist ◽  
Set Up ◽  
The Individual ◽  
New Literature ◽  
Current Systems

The entire field of information processing in medicine is today already spread out and branched to such an extent that it is no longer possible to set up a survey on relevant literature as a whole. But even in narrow parts of medical informatics it is hardly possible for the individual scientist to keep up to date with new literature. Strictly defined special bibliographies on certain topics are most helpful.In our days, problems of optimal patient scheduling and exploitation of resources are gaining more and more importance. Scientists are working on the solution of these problems in many places.The bibliography on »Patient Scheduling« presented here contains but a few basic theoretical papers on the problem of waiting queues which are of importance in the area of medical care. Most of the papers cited are concerned with practical approaches to a solution and describe current systems in medicine.In listing the literature, we were assisted by Mrs. Wieland, Mr. Dusberger and Mr. Henn, in data acquisition and computer handling by Mrs. Gieß and Mr. Schlaefer. We wish to thank all those mentioned for their assistance.

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

2017 ◽  
Author(s):  
Sabrina Jaeger ◽  
Simone Fulle ◽  
Samo Turk
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Supervised Machine Learning ◽  
Learning Approach ◽  
Learning Approaches ◽  
Unsupervised Machine Learning ◽  
Feature Representations ◽  
Machine Learning Approach ◽  
The Individual ◽  
Vector Representations

Inspired by natural language processing techniques we here introduce Mol2vec which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Similarly, to the Word2vec models where vectors of closely related words are in close proximity in the vector space, Mol2vec learns vector representations of molecular substructures that are pointing in similar directions for chemically related substructures. Compounds can finally be encoded as vectors by summing up vectors of the individual substructures and, for instance, feed into supervised machine learning approaches to predict compound properties. The underlying substructure vector embeddings are obtained by training an unsupervised machine learning approach on a so-called corpus of compounds that consists of all available chemical matter. The resulting Mol2vec model is pre-trained once, yields dense vector representations and overcomes drawbacks of common compound feature representations such as sparseness and bit collisions. The prediction capabilities are demonstrated on several compound property and bioactivity data sets and compared with results obtained for Morgan fingerprints as reference compound representation. Mol2vec can be easily combined with ProtVec, which employs the same Word2vec concept on protein sequences, resulting in a proteochemometric approach that is alignment independent and can be thus also easily used for proteins with low sequence similarities.

scholarly journals Nudge Versus Boost: Agency Dynamics Under Libertarian Paternalism

2019 ◽  
Vol 130 (629) ◽  
pp. 1384-1415 ◽  
Author(s):  
Ralph Hertwig ◽  
Michael D Ryall
Keyword(s):  
Cognitive Biases ◽  
Policy Implications ◽  
Best Interests ◽  
Libertarian Paternalism ◽  
The Future ◽  
Set Up ◽  
The Individual

ABSTRACT Thaler and Sunstein (2008) advance the concept of ‘nudge’ policies—non-regulatory and non-fiscal mechanisms designed to enlist people's cognitive biases or motivational deficits so as to guide their behaviour in a desired direction. A core assumption of this approach is that policymakers make artful use of people's cognitive biases and motivational deficits in ways that serve the ultimate interests of the nudged individual. We analyse a model of dynamic policymaking in which the policymaker's preferences are not always aligned with those of the individual. One novelty of our set-up is that the policymaker has the option to implement a ‘boost’ policy, equipping the individual with the competence to overcome the nudge-enabling bias once and for all. Our main result identifies conditions under which the policymaker chooses not to boost in order to preserve the option of using the nudge (and its associated bias) in the future—even though boosting is in the immediate best interests of both the policymaker and the individual. We extend our analysis to situations in which the policymaker can be removed (e.g., through an election) and in which the policymaker is similarly prone to bias. We conclude with a discussion of some policy implications of these findings.

A Comparison of Colectomy Outcomes Utilizing Open, Laparoscopic, and Robotic Techniques

2020 ◽  
pp. 000313482097338
Author(s):  
Elizabeth McCarthy ◽  
Benjamin L. Gough ◽  
Michael S. Johns ◽  
Alexandra Hanlon ◽  
Sachin Vaid ◽  
...  
Keyword(s):  
Postoperative Recovery ◽  
Logistic Regression Models ◽  
Community Institution ◽  
Physical Status Classification ◽  
Estimated Blood Loss ◽  
Comparative Review ◽  
Significant Difference ◽  
American Society ◽  
The Individual ◽  
American Society Of Anesthesiologists

Introduction Robotic colectomy could reduce morbidity and postoperative recovery over laparoscopic and open procedures. This comparative review evaluates colectomy outcomes based on surgical approach at a single community institution. Methods A retrospective review of all patients who underwent colectomy by a fellowship-trained colon and rectal surgeon at a single institution from 2015 through 2019 was performed, and a cohort developed for each approach (open, laparoscopic, and robotic). 30-day outcomes were evaluated. For dichotomous outcomes, univariate logistic regression models were used to quantify the individual effect of each predictor of interest on the odds of each outcome. Continuous outcomes received a similar approach; however, linear and Poisson regression modeling were used, as appropriate. Results 115 patients were evaluated: 14% (n = 16) open, 44% (n = 51) laparoscopic, and 42% (n = 48) robotic. Among the cohorts, there was no statistically significant difference in operative time, rate of reoperation, readmission, or major complications. Robotic colectomies resulted in the shortest length of stay (LOS) (Kruskal-Wallis P < .0001) and decreased estimated blood loss (EBL) (Kruskal-Wallis P = .0012). Median age was 63 years (interquartile range [IQR] 53-72). 54% (n = 62) were female. Median American Society of Anesthesiologists physical status classification was 3 (IQR 2-3). Median body mass index was 28.67 (IQR 25.03-33.47). A malignant diagnosis was noted on final pathology in 44% (n = 51). Conclusion Among the 3 approaches, there was no statistically significant difference in 30-day morbidity or mortality. There was a statistically significant decreased LOS and EBL for robotic colectomies.

scholarly journals Urinary Cytokines Reflect Renal Inflammation in Acute Tubulointerstitial Nephritis: A Multiplex Bead-Based Assay Assessment

2021 ◽  
Vol 10 (13) ◽  
pp. 2986
Author(s):  
Laura Martinez Valenzuela ◽  
Juliana Draibe ◽  
Oriol Bestard ◽  
Xavier Fulladosa ◽  
Francisco Gómez-Preciado ◽  
...  
Keyword(s):  
Tubulointerstitial Nephritis ◽  
Urinary Concentration ◽  
Blood Eosinophil ◽  
Acute Tubulointerstitial Nephritis ◽  
Luminex Assay ◽  
Non Invasive ◽  
Urinary Levels ◽  
Histological Data ◽  
The Individual ◽  
Multiplex Bead

Background: Acute tubulointerstitial nephritis (ATIN) diagnosis lays on histological assessment through a kidney biopsy, given the absence of accurate non-invasive biomarkers. The aim of this study was to evaluate the accuracy of different urinary inflammation-related cytokines for the diagnostic of ATIN and its distinction from acute tubular necrosis (ATN). Methods: We included 33 patients (ATIN (n = 21), ATN (n = 12)), and 6 healthy controls (HC). We determined the urinary levels of 10 inflammation-related cytokines using a multiplex bead-based Luminex assay at the time of biopsy and after therapy, and registered main clinical, analytical and histological data. Results: At the time of biopsy, urinary levels of I-TAC/CXCL11, CXCL10, IL-6, TNFα and MCP-1 were significantly higher in ATIN compared to HC. A positive correlation between the extent of the tubulointerstitial cellular infiltrates in kidney biopsies and the urinary concentration of I-TAC/CXCL11, MIG/CXCL9, CXCL10, IL17, IFNα, MCP1 and EGF was observed. Notably, I-TAC/CXCL11, IL-6 and MCP-1 were significantly higher in ATIN than in ATN, with I-TAC/CXCL11 as the best discriminative classifier AUC (0.77, 95% CI 0.57–0.95, p = 0.02). A combinatory model of these three urinary cytokines increased the accuracy in the distinction of ATIN/ATN compared to the individual biomarkers. The best model resulted when combining the three cytokines with blood eosinophil and urinary leukocyte counts (LR = 9.76). Follow-up samples from 11ATIN patients showed a significant decrease in I-TAC/CXCL11, MIG/CXCL9 and CXCL10 levels. Conclusions: Urinary I-TAC/CXCL11, CXCL10, IL6 and MCP-1 levels accurately distinguish patients developing ATIN from ATN and healthy individuals and may serve as novel non-invasive biomarkers in this disease.

scholarly journals Public Roads as Places of Interspecies Conflict: A Study of Horse-Human Interactions on UK Roads and Impacts on Equine Exercise

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1072
Author(s):  
Danica Pollard ◽  
Tamzin Furtado
Keyword(s):  
Near Miss ◽  
Online Questionnaire ◽  
Near Misses ◽  
Logistic Regression Models ◽  
Emotional Management ◽  
The Road ◽  
Human Interactions ◽  
Road Users ◽  
Conflict Risk ◽  
The Individual

Real or perceived traffic risk is a significant barrier to walking and cycling. To understand whether similar barriers influence equestrians, this study obtained exercise behaviours, road use and experiences of road-related incidents from UK equestrians (n = 6390) via an online questionnaire. Multivariable logistic regression models were used to identify factors associated with road use and experiencing a near-miss or injury-causing incident in the previous year. Content analysis identified themes around equestrians’ decisions not to use roads. Our results show that most equestrians (84%) use roads at least once weekly, and in the previous year, 67.7% had a near-miss and 6.1% an injury-causing incident. Road use differs regionally, with exercise type and off-road route availability. Road-using equestrians covered greater daily distances and were younger. However, younger equestrians were at higher risk of near-misses. Respondents’ decisions not to use roads were based on individualised risk assessments arising from: the road itself, perceptions of other road users, the individual horse and the handler’s own emotional management. Roads were perceived as extremely dangerous places with potentially high conflict risk. Injury-causing incidents were associated with increasing road-use anxiety or ceasing to use roads, the proximity of off-road routes, having a near-miss and type of road use. Targeted road-safety campaigns and improved off-road access would create safer equestrian spaces.

Comparable Outcomes of Short-Course and Prolonged-Course Therapy in Selected Cases of Methicillin-Susceptible Staphylococcus aureus Bacteremia: A Pooled Cohort Study

2021 ◽  
Author(s):  
Louise Thorlacius-Ussing ◽  
Håkon Sandholdt ◽  
Jette Nissen ◽  
Jon Rasmussen ◽  
Robert Skov ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Clinical Outcomes ◽  
Treatment Duration ◽  
Cohort Analysis ◽  
Antimicrobial Treatment ◽  
Low Risk ◽  
Logistic Regression Models ◽  
Staphylococcus Aureus Bacteremia ◽  
Short Course ◽  
The Individual

Abstract Background The recommended duration of antimicrobial treatment for Staphylococcus aureus bacteremia (SAB) is a minimum of 14 days. We compared the clinical outcomes of patients receiving short-course (SC; 6–10 days), or prolonged-course (PC; 11–16 days) antibiotic therapy for low-risk methicillin-susceptible SAB (MS-SAB). Methods Adults with MS-SAB in 1995–2018 were included from 3 independent retrospective cohorts. Logistic regression models fitted with inverse probability of treatment weighting were used to assess the association between the primary outcome of 90-day mortality and treatment duration for the individual cohorts as well as a pooled cohort analysis. Results A total of 645, 219, and 141 patients with low-risk MS-SAB were included from cohorts I, II, and III. Median treatment duration in the 3 SC groups was 8 days (interquartile range [IQR], 7–10), 9 days (IQR, 8–10), and 8 days (IQR, 7–10). In the PC groups, patients received a median therapy of 14 days (IQR, 13–15), 14 days (IQR, 13–15), and 13 days (IQR, 12–15). No significant differences in 90-day mortality were observed between the SC and PC group in cohort I (odds ratio [OR], 0.85 [95% confidence interval {CI}, .49–1.41]), cohort II (OR, 1.24 [95% CI, .60–2.62]), or cohort III (OR, 1.15 [95% CI, .24–4.01]). This result was consistent in the pooled cohort analysis (OR, 1.05 [95% CI, .71–1.51]). Furthermore, duration of therapy was not associated with the risk of relapse. Conclusions In patients with low-risk MS-SAB, shorter courses of antimicrobial therapy yielded similar clinical outcomes as longer courses of therapy.

scholarly journals Hydraulic insertions of cochlear implant electrode arrays into the human cadaver cochlea: preliminary findings

2021 ◽  
Author(s):  
M. Geraldine ◽  
Thomas Lenarz ◽  
Thomas S. Rau
Keyword(s):  
Cochlear Implant ◽  
Outcome Measurement ◽  
Round Window ◽  
Handling Time ◽  
Human Cadaver ◽  
Hydraulic Actuator ◽  
Electrode Arrays ◽  
Non Invasive ◽  
Insertion Tool ◽  
Set Up

Abstract Objectives (1) To evaluate the feasibility of a non-invasive, novel, simple insertion tool to perform automated, slow insertions of cochlear implant electrode arrays (EA) into a human cadaver cochlea; (2) to estimate the handling time required by our tool. Methods Basic science study conducted in an experimental OR. Two previously anonymized human cadaver heads, three commercially available EAs, and our novel insertion tool were used for the experiments. Our tool operates as a hydraulic actuator that delivers an EA at continuous velocities slower than manually feasible. Intervention(s): the human cadaver heads were prepared with a round-window approach for CI surgery in a standard fashion. Twelve EA insertion trials using our tool involved: non-invasive fixation of the tool to the head; directing the tool to the round window and EA mounting onto the tool; automated EA insertion at approximately 0.1 mm/s driven by hydraulic actuation. Outcome measurement(s): handling time of the tool; post-insertion cone-beam CT scans to provide intracochlear evaluation of the EA insertions. Results Our insertion tool successfully inserted an EA into the human cadaver cochlea (n = 12) while being attached to the human cadaver head in a non-invasive fashion. Median time to set up the tool was 8.8 (7.2–9.4) min. Conclusion The first insertions into the human cochlea using our novel, simple insertion tool were successful without the need for invasive fixation. The tool requires < 10 min to set up, which is clinically acceptable. Future assessment of intracochlear trauma is needed to support its safety profile for clinical translation.

scholarly journals Joint bodies in the European Union's international agreements: Delegating powers to the European Commission in EU external relations

2021 ◽  
pp. 146511652110273
Author(s):  
Markus Gastinger ◽  
Andreas Dür
Keyword(s):  
European Union ◽  
European Commission ◽  
Empirical Support ◽  
International Agreements ◽  
Principal Agent ◽  
The European Union ◽  
Original Dataset ◽  
Voting Rule ◽  
External Relations ◽  
Set Up

In many international agreements, the European Union sets up joint bodies such as ‘association councils’ or ‘joint committees’. These institutions bring together European Union and third-country officials for agreement implementation. To date, we know surprisingly little about how much discretion the European Commission enjoys in them. Drawing on a principal–agent framework, we hypothesise that the complexity of agreements, the voting rule, conflict within the Council, and agency losses can explain Commission discretion in these institutions. Drawing on an original dataset covering nearly 300 such joint bodies set up by the European Union since 1992, we find robust empirical support for all expectations except for the agency loss thesis. Our findings suggest that the European Commission is the primary actor in the implementation of many of the European Union's international agreements, allowing it to influence EU external relations beyond what is currently acknowledged in the literature.

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