Chunqiang Wei et al. found that #Plant species of higher #IntrinsicGrowthAbility suffered greater negative #Soil effects, plant traits such as intrinsic growth ability, other than #PhylogeneticRelatedness, could be reliable #Predictors for plant responses to #SoilBiota, the soil biota on average had greater negative impacts on the #ExoticSpecies, particularly the #PerennialSpecies, than on the native species.
https://doi.org/10.1093/jpe/rtac044

'On Sufficient Graphical Models', by Bing Li, Kyongwon Kim.

http://jmlr.org/papers/v25/23-0893.html

#predictors #dimensionality #dimensional

On Sufficient Graphical Models

'Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction', by Jue Hou, Zijian Guo, Tianxi Cai.

http://jmlr.org/papers/v24/21-1075.html

#imputation #predictors #supervised

Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction

#Predictors of the #postCOVID condition following mild #SARS-CoV-2 infection, Nat Commun.: https://www.nature.com/articles/s41467-023-41541-x #research #science #covid19
Predictors of the post-COVID condition following mild SARS-CoV-2 infection - Nature Communications

In this study, the authors investigate the incidence and risk factors for post-COVID condition among people who had a mild initial SARS-CoV-2 infection in Norway. They use national linked registry data including ~215,000 individuals with a positive SARS-CoV-2 test who were not hospitalised and followed them up for 180 days after infection.

Nature

Exact and Approximate Conformal Inference for Multi-task Learning

https://openreview.net/forum?id=ixcW7aQNHl

#predictors #prediction #predictive

Exact and Approximate Conformal Inference for Multi-task Learning

It is common in machine learning to estimate a response $y$ given covariate information $x$. However, these predictions alone do not quantify any uncertainty associated with said predictions. One...

OpenReview

Using #ArtificialIntelligence to identify the top 50 independent #predictors of #subjective #WellBeing in a multinational sample of 37,991 older European & Israeli adults

#OpenAccess
#ScientificReports

"2 top-ranked SWB predictors were #social factors, which also had the highest overall group ranking, followed by #PhysicalHealth, #demographics, #FinancialStatus and #personality"

https://www.nature.com/articles/s41598-023-38337-w

Using artificial intelligence to identify the top 50 independent predictors of subjective well-being in a multinational sample of 37,991 older European & Israeli adults - Scientific Reports

Subjective well-being (SWB) is widely recognized as an important health outcome, but its complexity, myriad predictors, and analytic requirements pose significant challenges to identifying the relative order and impact of SWB determinants. This study involved a representative sample of 37,991 older adults from 17 European countries and Israel. An aggregate index of SWB was developed and compared across countries, and machine-learning algorithms were used to rank-order the strongest 50 (of an initial 94) SWB predictors from 15 categories. General Additive Modeling (GAM) and low-degree polynomials (i.e., splines) were used to determine the independent effect sizes and significance levels for each of these top-50 SWB predictors. Of the 18 countries included in this study, Denmark had the highest mean SWB, while Greece had the lowest. The two top-ranked SWB predictors (loneliness, social activity satisfaction) were social factors, which also had the highest overall group ranking, followed by physical health, demographics, financial status and personality. Self-reported health was the strongest health-related predictor, neuroticism was the strongest personality predictor, and women reported higher SWB than men. SWB decreased with age, and increased with income up to 350,000 euros/year, after which it declined. Social factors were of primary importance for subjective well-being in this research, while childhood experiences and healthcare status exerted the smallest effects. The vast majority of the top 50 SWB predictors were statistically significant, with the notable exceptions of body mass index and most health behaviors, which may impact SWB indirectly through their effects on physical health. Future multivariate modeling is recommended to clarify the mechanisms for these and other observed relationships.

Nature

'The Implicit Bias of Benign Overfitting', by Ohad Shamir.

http://jmlr.org/papers/v24/22-0784.html

#overfitting #predictors #predictor

The Implicit Bias of Benign Overfitting

Using Satellite Data For Species Distribution Modeling With GRASS GIS And R [video tutorial]
--
https://youtu.be/MLhrhUfPzZk <-- shared tutorial video
--
“Species distribution models (SDM) have traditionally used climatic data as predictors of habitat suitability for the target species. In this hands-on studio, ‘we’ will explore the use of satellite data to derive relevant predictors. ‘We’ will perform satellite data processing, from download to analysis, using GRASS GIS software functionality. Then, ‘we’ll’ read our predictors within R and perform SDM, visualize and analyze results. Finally, ‘we’ will write the output distribution maps back into GRASS…”
#GIS #spatial #mapping #spatialanalysis #tutorial #onlinelearning #software #video #R #SDM #speciesdistributionmodel #GRASS #model #modeling #remotesensing #satellite #predictors #dataprocessing #download #opendata #openaccess #opensource #visualisation #map
Geospatial Forum (Studio): Dr. Verónica Andreo

YouTube
[Articles] #Outcome #predictors and patient progress following delivery in #pregnant and #postpartum patients with severe #COVID19 #pneumonitis in #ICUs in #Israel (OB-COVICU): a nationwide cohort study https://www.thelancet.com/journals/lanres/article/PIIS2213-2600(22)00491-X/fulltext?rss=yes