Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Researchers developed a new model to predict the likelihood of critical illness in patients with connective-tissue disease-associated ILD.
An artificial intelligence (AI) machine-learning model has been developed that can predict the risk of early death in trauma ...
Reports demonstrates that whole-brain Single Photon Emission Computed Tomography (SPECT) imaging, combined with advanced ...
The image shows the proposed IoT-enabled real-time building fire detection system, integrating MQ-2 smoke sensing, DHT11 temperature and humidity sensing, NodeMCU ESP8266 control, relay-based alarm ...
Glucose-to-potassium ratio shows a J-shaped link with AKI after traumatic brain injury, with high levels predicting increased ...
Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
Abstract: This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random ...
Analyzing thousands of proteins from a single drop of blood is no longer science fiction. High-throughput proteomics has transformed biomarker discovery by enabling simultaneous profiling of thousands ...
Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
Application of Random Forest Algorithm on Feature Subset Selection and Classification and Regression
Abstract: Feature subset selection becomes quite important and predominant in the case of data sets those are contained with higher number of variables. It discards insignificant variables and ...
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