Efficient Learning Algorithms for the Best Capped Base-Stock Policy in Lost Sales Inventory Systems Periodic review, lost sales inventory systems with lead times are notoriously challenging to ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
When it comes to machine learning, there are some broad concepts and terms that everyone in search should know. We should all know where machine learning is used, and the different types of machine ...
In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...
Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...
When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...
Ben Khalesi writes about where artificial intelligence, consumer tech, and everyday technology intersect for Android Police. With a background in AI and Data Science, he’s great at turning geek speak ...
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