Results 231 to 240 of about 137,972 (308)

Ensemble machine learning method for δ¹⁸O prediction in groundwater. [PDF]

Sci Rep
Mohamed FA, Sadek M, Kandil NM.
europepmc   +1 more source

Maize Kernel Composition and Morphology Influences Pericarp Retention During Nixtamalization

Cereal Chemistry, EarlyView.
Abstract Background and Objectives Pericarp retention during nixtamalization directly influences masa quality, affecting texture, machinability, and nutritional content of staple foods such as tortillas and chips. Despite its industrial relevance, the underlying kernel traits that govern pericarp retention remain poorly characterized.
Michael J. Burns, Sydney P. Berry, Amanda M. Gilbert, Peter J. Hermanson, Candice N. Hirsch   +4 more
wiley   +1 more source

Ensemble learning uncovers novel metabolomic biomarkers for early osteoporosis prediction in Tibetan plateau populations. [PDF]

Metabol Open
Yang J, Zhou T, Zhang H, Zhang Q, Chen L, Xiao Q, Luo S, Labasangzhu, Dunyou, Danbalangjie, Hao W, Wei X.   +11 more
europepmc   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Comparison of Feature Selection Methods in Machine Learning Models of Cancer Information Seeking Among United States Adults: Cross-Sectional Study. [PDF]

JMIR Med Inform
Liu Y, Wang K.
europepmc   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

The Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan, Ryan Gosselin, Nicolas Abatzoglou   +2 more
wiley   +1 more source

A LASSO-based nomogram for predicting acute bilirubin encephalopathy in newborns with severe hyperbilirubinemia. [PDF]

Front Pediatr
Hu Q, Yao Z, Zhu H, Feng X, Li H.
europepmc   +1 more source

Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions

Canadian Journal of Statistics, EarlyView.
Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni, Luca Merlo, Lea Petrella   +2 more
wiley   +1 more source

Prognostic Models for Small Hepatocellular Carcinoma Using Inflammatory Indices and Machine Learning: A Propensity Score-Matched Study. [PDF]

Int J Gen Med
Cong Y, Gou Y, Ma Z, Huang W, Zhang L, Guo Q, Aji T, Shao Y.   +7 more
europepmc   +1 more source