To undertake a reliable analysis of injury severity in road traffic accidents, a complete understanding of important attributes is essential. As a result of the shift from traditional statistical parametric procedures to computer-aided methods, machi...
Artificial intelligence (AI) is a broad term referring to the application of computational algorithms that can analyze large data sets to classify, predict, or gain useful conclusions. Under the umbrella of AI is machine learning (ML). ML is the proc...
Computer methods and programs in biomedicine
Feb 1, 2022
BACKGROUND AND OBJECTIVES: Photoplethysmography (PPG) is a device that measures the amount of light absorbed by the blood vessel, blood, and tissues, which can, in turn, translate into various measurements such as the variation in blood flow volume, ...
Damage detection based on modal parameter changes has become popular in the last few decades. Nowadays, there are robust and reliable mathematical relations available to predict natural frequency changes if damage parameters are known. Using these re...
Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. R...
Computer methods in biomechanics and biomedical engineering
Jan 31, 2022
Nowadays, deep learning methods with transfer learning (TL) makes ease of stress emotion classification tasks. Amongst, an optimized convolutional neural network with TL (OCNNTL) executes OCNN-based classification on emotion and stress data domains t...
DNA N4-methylcytosine (4mC) is an important DNA modification and plays a crucial role in a variety of biological processes. Accurate 4mC site identification is fundamental to improving the understanding of 4mC biological functions and mechanisms. How...
BACKGROUND: Unnecessary laboratory tests contribute to iatrogenic harm and are a major source of waste in the health care system. We previously developed a machine learning algorithm to help clinicians identify unnecessary laboratory tests, but it ha...
Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple...
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