Enhanced geographical features improve predictive models for colorectal cancer survival curves.
problem Predicting colorectal cancer survival curves in Iowa.
method Used neural networks to explore feature representations, comparing ABC performance.
result Spectral analysis-based representations improve predictive performance by approximately 40%.
Study improves fraud detection in e-commerce with a stacked model combining CNNs, GNNs, and confidence gating.
problem Detecting credit card fraud in online transactions.
method Stacking approach with attention and confidence-driven layers, using DOWA and IOWA operators.
result The method achieves high accuracy and robust generalization in CCF detection.
Corn yield prediction is beneficial as it provides valuable information about production and prices prior the harvest. Publicly available high-quality corn yield prediction can help address emergent information asymmetry problems and in doing so improve price efficiency in futures markets. This paper is the first to em…
We develop a model of how information flows into a market, and derive algorithms for automatically detecting and explaining relevant events. We analyze data from twenty-two "political stock markets" (i.e., betting markets on political outcomes) on the Iowa Electronic Market (IEM). We prove that, under certain efficienc…
Study forecasts cardiology admissions from cath lab using ARIMA models.
problem Complexity in managing cardiology admissions from cath lab.
method Retrospective data analysis with ARIMA, Holts method, and other models.
result ARIMA (2,0,2) (1,1,1) model selected as best fit.
Study analyzes climate impact on agricultural prices, offering insurance solutions.
problem Financial risk from climate-induced agricultural price volatility.
method Historical and future climate projections, EGARCH and SARIMAX models, Black-Scholes framework.
result Improved agricultural risk modeling and insurance mechanisms.
Unified framework detects overfitting in crash classification models.
problem Evaluation metrics fail to detect overfitting in crash classification models.
method Random Matrix Theory and Heavy-Tailed Self-Regularization framework applied to various model types.
result Power-law exponent α reliably distinguishes well-regularized from overfit models.
Study models weather index insurance pricing by insurers and farmers, finding flexible pricing kernels boost profits.
problem Monopoly pricing of weather index insurance with risk and flexibility considerations.
method Bowley-type sequential game with insurer and farmer, using neural networks for farmer's payoff.
result Flexible pricing kernels increase insurer profits closer to indemnity insurance levels.
Crop yield forecasting is the methodology of predicting crop yields prior to harvest. The availability of accurate yield prediction frameworks have enormous implications from multiple standpoints, including impact on the crop commodity futures markets, formulation of agricultural policy, as well as crop insurance ratin…
Bayesian model tackles spatial count data issues with flexible non-parametric techniques.
problem Challenges in traditional parametric models for spatial count data with unbalanced distributions and complex dependencies.
method Bayesian semi-parametric spatial dispersed count model combining non-parametric techniques and adapted count models.
result Demonstrates superior performance in managing dispersion and capturing intricate spatial patterns.
Paper presents a machine learning framework for corn yield forecasting.
problem Accurate and timely prediction of corn yields in the US Corn Belt.
method Machine learning ensembles considering complete and partial in-season weather data.
result Ensemble models outperform individual models, achieving best prediction accuracy.