AIMC Topic: Machine Learning

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The applications of deep learning algorithms on in silico druggable proteins identification.

Journal of advanced research
INTRODUCTION: The top priority in drug development is to identify novel and effective drug targets. In vitro assays are frequently used for this purpose; however, traditional experimental approaches are insufficient for large-scale exploration of nov...

An AI-based Prediction Model for Drug-drug Interactions in Osteoporosis and Paget's Diseases from SMILES.

Molecular informatics
The skeleton is one of the most important organs in the human body in assisting our motion and activities; however, bone density attenuates gradually as we age. Among common bone diseases are osteoporosis and Paget's, two of the most frequently found...

Chemical Reactivity Prediction: Current Methods and Different Application Areas.

Molecular informatics
The ability to predict chemical reactivity of a molecule is highly desirable in drug discovery, both ex vivo (synthetic route planning, formulation, stability) and in vivo: metabolic reactions determine pharmacodynamics, pharmacokinetics and potentia...

Predicting Continuity of Asthma Care Using a Machine Learning Model: Retrospective Cohort Study.

International journal of environmental research and public health
Continuity of care (COC) has been shown to possess numerous health benefits for chronic diseases. Specifically, the establishment of its level can facilitate clinical decision-making and enhanced allocation of healthcare resources. However, the use o...

Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States.

Environmental science and pollution research international
Natural streams longitudinal dispersion coefficient (Kx) is an essential indicator for pollutants transport and its determination is very important. Kx is influenced by several parameters, including river hydraulic geometry, sediment properties, and ...

Inpainted Image Reconstruction Using an Extended Hopfield Neural Network Based Machine Learning System.

Sensors (Basel, Switzerland)
This paper considers the use of a machine learning system for the reconstruction and recognition of distorted or damaged patterns, in particular, images of faces partially covered with masks. The most up-to-date image reconstruction structures are ba...

Twenty seconds of visual behaviour on social media gives insight into personality.

Scientific reports
Eye tracking allows the researcher to capture individual differences in the expression of visual exploration behaviour, which in certain contexts has been found to reflect aspects of the user's preferences and personality. In a novel approach, we rec...

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Scientific reports
Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity. Interventions initiated early in pregnancy can reduce the rate of GDM i...

Early identification of older individuals at risk of mobility decline with machine learning.

Archives of gerontology and geriatrics
BACKGROUND: The early identification of individuals at risk of mobility decline can improve targeted strategies of prevention.

Machine learning classification of trajectories from molecular dynamics simulations of chromosome segregation.

PloS one
In contrast to the well characterized mitotic machinery in eukaryotes it seems as if there is no universal mechanism organizing chromosome segregation in all bacteria. Apparently, some bacteria even use combinations of different segregation mechanism...