AIMC Topic: Machine Learning

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How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information.

Journal of biomedical informatics
It is believed that anomalous mental states such as stress and anxiety not only cause suffering for the individuals, but also lead to tragedies in some extreme cases. The ability to predict the mental state of an individual at both current and future...

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

Journal of chemical information and modeling
The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most ofte...

Machine Learning Principles Can Improve Hip Fracture Prediction.

Calcified tissue international
Apply machine learning principles to predict hip fractures and estimate predictor importance in Dual-energy X-ray absorptiometry (DXA)-scanned men and women. Dual-energy X-ray absorptiometry data from two Danish regions between 1996 and 2006 were com...

Using data from the Microsoft Kinect 2 to determine postural stability in healthy subjects: A feasibility trial.

PloS one
The objective of this study was to determine whether kinematic data collected by the Microsoft Kinect 2 (MK2) could be used to quantify postural stability in healthy subjects. Twelve subjects were recruited for the project, and were instructed to per...

Extreme learning machine based optimal embedding location finder for image steganography.

PloS one
In image steganography, determining the optimum location for embedding the secret message precisely with minimum distortion of the host medium remains a challenging issue. Yet, an effective approach for the selection of the best embedding location wi...

Data-driven system to predict academic grades and dropout.

PloS one
Nowadays, the role of a tutor is more important than ever to prevent students dropout and improve their academic performance. This work proposes a data-driven system to extract relevant information hidden in the student academic data and, thus, help ...

An interactive medical image segmentation framework using iterative refinement.

Computers in biology and medicine
Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results...

Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an e...

Comparison of models for predicting the changes in phytoplankton community composition in the receiving water system of an inter-basin water transfer project.

Environmental pollution (Barking, Essex : 1987)
Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water...

Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports.

Artificial intelligence in medicine
OBJECTIVE: Drug-drug interaction (DDI) is of serious concern, causing over 30% of all adverse drug reactions and resulting in significant morbidity and mortality. Early discovery of adverse DDI is critical to prevent patient harm. Spontaneous reporti...