RED: A Simple but Effective Baseline Predictor for the TrajNet Benchmark

2019 ◽  
pp. 138-153 ◽  
Author(s):  
Stefan Becker ◽  
Ronny Hug ◽  
Wolfgang Hübner ◽  
Michael Arens
Keyword(s):  
Baseline Predictor

Comparative Analysis of the Influence of Stress-Related Variables on Adaptation to a New Work Setting

1988 ◽  
Vol 63 (3) ◽  
pp. 767-777 ◽  
Author(s):  
Jan Zahrly ◽  
Henry Tosi
Keyword(s):  
Job Satisfaction ◽  
Comparative Analysis ◽  
Role Conflict ◽  
Emotional Exhaustion ◽  
Role Ambiguity ◽  
Predictor Variables ◽  
Work Setting ◽  
New Work ◽  
Mode Of Entry ◽  
Baseline Predictor

The incremental effects of stress-related variables on adaptation to a new work setting were compared after 4 and 8 mo. Adaptation to the new work setting was assessed by job satisfaction and emotional exhaustion. Baseline predictor variables were shift, mode of entry (individual or group), job variety, and level of skills used by the organization. Stress-related predictor variables were role conflict, role ambiguity, and perceived symptoms of stress. Subjects were 80 employees at a new manufacturing facility. Comparative analysis indicated that role conflict was a significant factor in the prediction of job satisfaction and emotional exhaustion; symptoms of stress influenced emotional exhaustion. Role ambiguity was a poor predictor of job satisfaction and emotional exhaustion.

scholarly journals Developing a COVID-19 mortality risk prediction model when individual-level data are not available

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Noam Barda ◽  
Dan Riesel ◽  
Amichay Akriv ◽  
Joseph Levy ◽  
Uriah Finkel ◽  
...  
Keyword(s):  
Case Fatality ◽  
Operating Characteristics ◽  
Hybrid Strategy ◽  
Individual Level ◽  
Level Data ◽  
Receiver Operating Characteristics Curve ◽  
Severe Respiratory Infection ◽  
Baseline Predictor ◽  
Risk Predictor ◽  
Risk Predictors

Abstract At the COVID-19 pandemic onset, when individual-level data of COVID-19 patients were not yet available, there was already a need for risk predictors to support prevention and treatment decisions. Here, we report a hybrid strategy to create such a predictor, combining the development of a baseline severe respiratory infection risk predictor and a post-processing method to calibrate the predictions to reported COVID-19 case-fatality rates. With the accumulation of a COVID-19 patient cohort, this predictor is validated to have good discrimination (area under the receiver-operating characteristics curve of 0.943) and calibration (markedly improved compared to that of the baseline predictor). At a 5% risk threshold, 15% of patients are marked as high-risk, achieving a sensitivity of 88%. We thus demonstrate that even at the onset of a pandemic, shrouded in epidemiologic fog of war, it is possible to provide a useful risk predictor, now widely used in a large healthcare organization.

scholarly journals Pretreatment multi-biomarker disease activity score and radiographic progression in early RA: results from the SWEFOT trial

2014 ◽  
Vol 74 (6) ◽  
pp. 1102-1109 ◽  
Author(s):  
Karen Hambardzumyan ◽  
Rebecca Bolce ◽  
Saedis Saevarsdottir ◽  
Scott E Cruickshank ◽  
Eric H Sasso ◽  
...  
Keyword(s):  
Disease Activity ◽  
Disease Activity Score ◽  
Radiographic Progression ◽  
Independent Predictor ◽  
Optimal Choice ◽  
Activity Score ◽  
Karolinska Institute ◽  
Reactive Protein ◽  
Registration Number ◽  
Baseline Predictor

ObjectivesPrediction of radiographic progression (RP) in early rheumatoid arthritis (eRA) would be very useful for optimal choice among available therapies. We evaluated a multi-biomarker disease activity (MBDA) score, based on 12 serum biomarkers as a baseline predictor for 1-year RP in eRA.MethodsBaseline disease activity score based on erythrocyte sedimentation rate (DAS28-ESR), disease activity score based on C-reactive protein (DAS28-CRP), CRP, MBDA scores and DAS28-ESR at 3 months were analysed for 235 patients with eRA from the Swedish Farmacotherapy (SWEFOT) clinical trial. RP was defined as an increase in the Van der Heijde-modified Sharp score by more than five points over 1 year. Associations between baseline disease activity measures, the MBDA score, and 1-year RP were evaluated using univariate and multivariate logistic regression, adjusted for potential confounders.ResultsAmong 235 patients with eRA, 5 had low and 29 moderate MBDA scores at baseline. None of the former and only one of the latter group (3.4%) had RP during 1 year, while the proportion of patients with RP among those with high MBDA score was 20.9% (p=0.021). Among patients with low/moderate CRP, moderate DAS28-CRP or moderate DAS28-ESR at baseline, progression occurred in 14%, 15%, 14% and 15%, respectively. MBDA score was an independent predictor of RP as a continuous (OR=1.05, 95% CI 1.02 to 1.08) and dichotomised variable (high versus low/moderate, OR=3.86, 95% CI 1.04 to 14.26).ConclusionsIn patients with eRA, the MBDA score at baseline was a strong independent predictor of 1-year RP. These results suggest that when choosing initial treatment in eRA the MBDA test may be clinically useful to identify a subgroup of patients at low risk of RP.Trial registration numberWHO database at the Karolinska Institute: CT20080004; and clinicaltrials.gov: NCT00764725.

scholarly journals Normalizing Item-Based Collaborative Filter Using Context-Aware Scaled Baseline Predictor

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Wenming Ma ◽  
Junfeng Shi ◽  
Ruidong Zhao
Keyword(s):  
Recommendation Systems ◽  
Basic Component ◽  
Experimental Results ◽  
Context Information ◽  
Context Aware ◽  
Collaborative Filter ◽  
Normalization Methods ◽  
Predictor Models ◽  
Baseline Predictor ◽  
Filter Algorithms

Item-based collaborative filter algorithms play an important role in modern commercial recommendation systems (RSs). To improve the recommendation performance, normalization is always used as a basic component for the predictor models. Among a lot of normalizing methods, subtracting the baseline predictor (BLP) is the most popular one. However, the BLP uses a statistical constant without considering the context. We found that slightly scaling the different components of the BLP separately could dramatically improve the performance. This paper proposed some normalization methods based on the scaled baseline predictors according to different context information. The experimental results show that using context-aware scaled baseline predictor for normalization indeed gets better recommendation performance, including RMSE, MAE, precision, recall, and nDCG.

scholarly journals Erythrocyte Sedimentation Rate as Baseline Predictor for the Development of Uveitis in Children With Juvenile Idiopathic Arthritis

2015 ◽  
Vol 159 (2) ◽  
pp. 372-377.e1 ◽  
Author(s):  
Arenda J.W. Haasnoot ◽  
Maretta van Tent-Hoeve ◽  
Nico M. Wulffraat ◽  
Nicoline E. Schalij-Delfos ◽  
Leonoor I. Los ◽  
...  
Keyword(s):  
Juvenile Idiopathic Arthritis ◽  
Erythrocyte Sedimentation Rate ◽  
Sedimentation Rate ◽  
Erythrocyte Sedimentation ◽  
Baseline Predictor

Exact Mean Absolute Error of Baseline Predictor, MARP0

2016 ◽  
Vol 73 ◽  
pp. 16-18 ◽  
Author(s):  
William B. Langdon ◽  
Javier Dolado ◽  
Federica Sarro ◽  
Mark Harman
Keyword(s):  
Mean Absolute Error ◽  
Absolute Error ◽  
Baseline Predictor

scholarly journals H i study of isolated and paired galaxies: the MIR SFR-M⋆ sequence

2020 ◽  
Vol 499 (3) ◽  
pp. 3193-3213
Author(s):  
J Bok ◽  
R E Skelton ◽  
M E Cluver ◽  
T H Jarrett ◽  
M G Jones ◽  
...  
Keyword(s):  
Star Formation ◽  
Star Formation Rate ◽  
Formation Rate ◽  
Stellar Mass ◽  
Wide Field ◽  
Fraction H ◽  
Isolated Galaxies ◽  
Baseline Predictor ◽  
Stellar Masses ◽  
The Impact

ABSTRACT Using mid-infrared star formation rate and stellar mass indicators in WISE (Wide-field Infrared Survey Explorer), we construct and contrast the relation between star formation rate and stellar mass for isolated and paired galaxies. Our samples comprise a selection of AMIGA (Analysis of the interstellar Medium in Isolated GAlaxies; isolated galaxies) and pairs of ALFALFA (Arecibo Legacy Fast ALFA) galaxies with H i detections such that we can examine the relationship between H i content (gas fraction, H i deficiency) and galaxy location on the main sequence (MS) in these two contrasting environments. We derive for the first time an H i scaling relation for isolated galaxies using WISE stellar masses, and thereby establish a baseline predictor of H i content that can be used to assess the impact of environment on H i content when compared with samples of galaxies in different environments. We use this updated relation to determine the H i deficiency of both our paired and isolated galaxies. Across all the quantities examined as a function of environment in this work (MS location, gas fraction, and H i deficiency), the AMIGA sample of isolated galaxies is found to have the lower dispersion: σAMIGA = 0.37 versus σPAIRS = 0.55 on the MS, σAMIGA = 0.44 versus σPAIRS = 0.54 in gas fraction, and σAMIGA = 0.28 versus σPAIRS = 0.34 in H i deficiency. We also note fewer isolated quiescent galaxies, 3 (0.6${{\ \rm per\ cent}}$), compared to 12 (2.3${{\ \rm per\ cent}}$) quiescent pair members. Our results suggest the differences in scatter measured between our samples are environment driven. Galaxies in isolation behave relatively predictably, and galaxies in more densely populated environments adopt a more stochastic behaviour, across a broad range of quantities.

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