AIMC Topic: Machine Learning

Clear Filters Showing 13881 to 13890 of 34417 articles

Interpretable machine learning for psychological research: Opportunities and pitfalls.

Psychological methods
In recent years, machine learning methods have become increasingly popular prediction methods in psychology. At the same time, psychological researchers are typically not only interested in making predictions about the dependent variable, but also in...

Using machine learning to improve Q-matrix validation.

Behavior research methods
The Q-matrix, which specifies the relationship between items and attributes, is a crucial component of cognitive diagnostic models (CDMs). A precisely specified Q-matrix allows for valid cognitive diagnostic assessments. In practice, a Q-matrix is us...

Prediction of heavy metals adsorption by hydrochars and identification of critical factors using machine learning algorithms.

Bioresource technology
Hydrochar has become a popular product for immobilizing heavy metals in water bodies. However, the relationships between the preparation conditions, hydrochar properties, adsorption conditions, heavy metal types, and the maximum adsorption capacity (...

Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

The British journal of radiology
OBJECTIVES: Current state-of-the-art natural language processing (NLP) techniques use transformer deep-learning architectures, which depend on large training datasets. We hypothesized that traditional NLP techniques may outperform transformers for sm...

Process identification and discrimination in the environmental dose rate time series of a radiopharmaceutical facility using machine learning techniques.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Multi-facility nuclear sites with research reactors have several environmental area gamma monitors in a network as a part of their surveillance capability. However, the routine release of low levels of Ar gas from the reactor is prone to interfere wi...

Counting Activities Using Weakly Labeled Raw Acceleration Data: A Variable-Length Sequence Approach with Deep Learning to Maintain Event Duration Flexibility.

Sensors (Basel, Switzerland)
This paper presents a novel approach for counting hand-performed activities using deep learning and inertial measurement units (IMUs). The particular challenge in this task is finding the correct window size for capturing activities with different du...

Multi-Modal Deep Learning Diagnosis of Parkinson's Disease-A Systematic Review.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Parkinson's Disease (PD) is among the most frequent neurological disorders. Approaches that employ artificial intelligence and notably deep learning, have been extensively embraced with promising outcomes. This study dispenses an exhaustive review be...

Advancing Computational Toxicology by Interpretable Machine Learning.

Environmental science & technology
Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals have a critical impact on human health. Traditional animal models to evaluate chemical toxicity are expensive, time-consuming, and often fail to detect toxicants ...

SGCL: Spatial guided contrastive learning on whole-slide pathological images.

Medical image analysis
Self-supervised representation learning (SSL) has achieved remarkable success in its application to natural images while falling behind in performance when applied to whole-slide pathological images (WSIs). This is because the inherent characteristic...

NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis.

Computers in biology and medicine
This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) to solve optimal feature selection problems. The NSICA is a multi-objective and discrete version of the original Imperialist Competitive Algorithm (ICA) t...