The Michaelis constant KM describes the affinity of an enzyme for a specific substrate and is a central parameter in studies of enzyme kinetics and cellular physiology. As measurements of KM are often difficult and time-consuming, experimental estima...
Computational intelligence and neuroscience
Oct 19, 2021
Facial features are an effective representation of students' fatigue state, and the eye is more closely related to fatigue state. However, there are three main problems in the existing research: (1) the positioning of the eye is vulnerable to the ext...
Computational intelligence and neuroscience
Oct 19, 2021
The electrocardiogram (ECG) is one of the most widely used diagnostic instruments in medicine and healthcare. Deep learning methods have shown promise in healthcare prediction challenges involving ECG data. This paper aims to apply deep learning tech...
The sudden rise in the ability of machine learning methodology, such as deep neural networks, to identify and predict with great accuracy instances of malignant cell growth from radiological images has led prominent developers of this technology, suc...
Neuropathology and applied neurobiology
Oct 18, 2021
AIMS: Although morphological attributes of cells and their substructures are recognised readouts of physiological or pathophysiological states, these have been relatively understudied in amyotrophic lateral sclerosis (ALS) research.
Environmental pollution (Barking, Essex : 1987)
Oct 18, 2021
The adverse health effects associated with the inhalation and ingestion of naturally occurring radon gas produced during the uranium decay chain mean that there is a need to identify high-risk areas. This study detected radon-prone areas using a geog...
Journal of biomolecular structure & dynamics
Oct 18, 2021
Heart disease (HD) is the major reason for the rampant cause of death around the world. It is deemed as a crucial illness among the middle and old age people which tends to high mortality rates. Recently, Effects of HD is presenting a shocking rise i...
In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a ...
The prerequisite of therapeutic drug design and discovery is to identify novel molecules and developing lead candidates with desired biophysical and biochemical properties. Deep generative models have demonstrated their ability to find such molecules...
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