Small area estimation of poverty severity index for Kecamatan (sub-district) in Surabaya city in 2020 using empirical best linear unbiased prediction method [PDF]
Nailatul Muna +2 more
openalex +1 more source
The (In)Effectiveness of Psychological Targeting: A Meta‐Analytic Review
ABSTRACT The use of psychological targeting—employing machine learning to predict consumer personality from digital footprints and subsequently tailoring persuasive messages—has emerged as a controversial yet prominent practice in digital marketing.
Raphael Perla +5 more
wiley +1 more source
GS4PB: An R Shiny application to facilitate a genomic selection pipeline for plant breeding. [PDF]
Ramasubramanian V +6 more
europepmc +1 more source
Mass Spectrometry Structural Proteomics Enabled by Limited Proteolysis and Cross‐Linking
ABSTRACT The exploration of protein structure and function stands at the forefront of life science and represents an ever‐expanding focus in the development of proteomics. As mass spectrometry (MS) offers readout of protein conformational changes at both the protein and peptide levels, MS‐based structural proteomics is making significant strides in the
Haiyan Lu +4 more
wiley +1 more source
Preliminary Evaluation of Blending, Tuning, and Scaling Parameters in ssGBLUP for Genomic Prediction Accuracy in South African Holstein Cattle. [PDF]
Mafolo KS +3 more
europepmc +1 more source
ABSTRACT Strategists who must identify issues in uncertain environments while being cognitively constrained can increasingly rely on artificial intelligence to manage uncertainty. The potential for AI to be incorporated into strategy processes has led to a debate about the evolving collaborative relationship between strategists and AI.
Thomas Hutzschenreuter +2 more
wiley +1 more source
Mean and variance heterogeneity loci impact kernel compositional traits in maize. [PDF]
Ismail YMA +5 more
europepmc +1 more source
Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu +3 more
wiley +1 more source
Personalized Differential Privacy for Ridge Regression Under Output Perturbation
ABSTRACT The increased application of machine learning (ML) in sensitive domains requires protecting the training data through privacy frameworks, such as differential privacy (DP). Traditional DP enforces a uniform privacy level ε$$ \varepsilon $$, which bounds the maximum privacy loss that each data point in the dataset is allowed to incur.
Krishna Acharya +3 more
wiley +1 more source

