Devdiscourse

High-accuracy AI models improve IoT threat detection

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Machine learning tool pinpoints optimal locations for tree planting, offering a powerful tool for climate mitigation

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...
Frontiers

Beyond the Algorithm: Scalable, Explainable, and Adaptive AI for High-Stakes Clinical Decision Support

Artificial Intelligence (AI) has shown strong potential in supporting clinical decision-making through Clinical Decision Support Systems (CDSSs). However, ...
Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
IEEE

MOCT: a Multi-class Oblique Tree Algorithm for Synergistic Drug Combination Prediction

Abstract: Machine learning has been successfully applied to drug combination prediction in recent years. However, in some situations, the class imbalance problem still shows highly negative impacts on ...
Visual Studio Magazine

Decision Tree Regression from Scratch Without Pointers or Recursion Using C#

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
The New York Times

Starting at Harvard and Falling for Your First Tree

A freshman seminar encourages students to behave differently in the world and feel more passionately about biodiversity. Each Harvard University freshman in the “Tree” seminar must choose a single ...
Frontiers

Clinical decision system for renal cell carcinoma integrating interpretable machine learning algorithms

Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and improve prognosis ...
C&EN

From Reaction Stoichiometry to Life Cycle Assessment: Decision Tree-Based Estimation Tool

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...
ahajournals.org

The Promise and Peril of Learning Algorithms and Predictive Models in Clinical Decision Support: Be Careful What You Train For

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical decision-making through the identification and ...
news.bloomberglaw

Navigating a Patent Gap for AI and Machine Learning Algorithms

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...