Ecotoxicology and environmental safety
Mar 20, 2023
Cancer, the second largest human disease, has become a major public health problem. The prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven machine learning algorithms (i.e., Random Forest (RF), Logistic R...
BACKGROUND: Autoencoder (AE) is one of the deep learning techniques that uses an artificial neural network to reconstruct its input data in the output layer. We constructed a novel supervised AE model and tested its performance in the prediction of a...
Confusion is the primary epistemic emotion in the learning process, influencing students' engagement and whether they become frustrated or bored. However, research on confusion in learning is still in its early stages, and there is a need to better u...
Understanding how plants respond to environmental conditions such as temperature, CO, humidity, and light radiation is essential for plant growth. This paper proposes an Artificial Neural Network (ANN) model to predict plant response to environmental...
INTRODUCTION: The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the prospect of increasing access to data and overcoming data privacy concerns when sharing data. The fie...
Computational intelligence and neuroscience
Mar 14, 2023
To diagnose an illness in healthcare, doctors typically conduct physical exams and review the patient's medical history, followed by diagnostic tests and procedures to determine the underlying cause of symptoms. Chronic kidney disease (CKD) is curren...
Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental...
Explainable artificial intelligence (XAI) is of paramount importance to various domains, including healthcare, fitness, skill assessment, and personal assistants, to understand and explain the decision-making process of the artificial intelligence (A...
BACKGROUND: Increasing access and better allocation of organs in the field of transplantation is a critical problem in clinical care. Limitations exist in accurately predicting allograft discard. Potential exists for machine learning to provide a bal...
Therapeutic innovation & regulatory science
Mar 3, 2023
The use of Bayesian statistics to support regulatory evaluation of medical devices began in the late 1990s. We review the literature, focusing on recent developments of Bayesian methods, including hierarchical modeling of studies and subgroups, borro...
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