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Hybrid model reveals people act less rationally in complex games, more predictably in simple ones
Throughout their everyday lives, humans are typically required to make a wide range of decisions, which can impact their well ...
IEEE2d
An Effective Heart Disease Detection and Severity Level Classification Model Using Machine Learning and Hyperparameter Optimization Methods - IEEE Xplore
Cardiovascular disease (CVD) is the leading cause of death worldwide. A Machine Learning (ML) system can predict CVD in the early stages to mitigate mortality rates based on clinical data. Recently, ...
Tech Xplore3d
Approach improves how new skills are taught to large language models
Researchers have developed a technique that significantly improves the performance of large language models without ...
IEEE4d
EEG mental arithmetic task levels classification using machine learning and deep learning algorithms - IEEE Xplore
EEG signals are often-used modalities for monitoring mental arithmetic performance. In order to learn robust characteristics and predict the level of classification from EEG, we provide a deep neural ...
eLife15d
Learning and cognition in highspeed decision making | eLife
It is widely accepted that more time and information yield better decisions. However, some decisions manage to be extremely fast and yet accurate. The trick of such highspeed decisions appears to be ...
C&EN17d
Small Data Machine Learning: Classification and Prediction of Poly(ethylene terephthalate) Stabilizers Using Molecular Descriptors
Experimental data from a patent were analyzed to learn about the small molecule additives that were most effective in mitigating the degradation of polyethylene terephthalate. Two sets of molecular ...
Frontiers22d
Predicting the hospitalization burdens of patients with mental disease: a multiple model comparison - Frontiers
Categorical boosting regression (CBR) is based on the gradient of decision tree machine learning algorithms, and it is especially suitable for processing that includes classification variable datasets ...
The Lancet27d
Comparison of machine learning and human prediction to identify trauma ...
The prospective ShockMatrix temporal validation study suggests a comparable human and machine learning performance to predict the need for HCR using real-life and real-time information with a moderate ...
SciELO28d
COMPUTATIONAL VISION FOR TOMATO CLASSIFICATION USING A DECISION TREE ALGORITHM - SciELO - Brasil
ABSTRACT Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify ...