AIMC Topic: Machine Learning

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Artificial intelligence and machine learning on diagnosis and classification of hip fracture: systematic review.

Journal of orthopaedic surgery and research
BACKGROUND: In the emergency room, clinicians spend a lot of time and are exposed to mental stress. In addition, fracture classification is important for determining the surgical method and restoring the patient's mobility. Recently, with the help of...

Ten quick tips for sequence-based prediction of protein properties using machine learning.

PLoS computational biology
The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences. Over the years, while revising our own work, reading submitted m...

Prediction of radiosensitivity and radiocurability using a novel supervised artificial neural network.

BMC cancer
BACKGROUND: Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a l...

A regression-based machine learning approach for pH and glucose detection with redox-sensitive colorimetric paper sensors.

Analytical methods : advancing methods and applications
Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner. However, these sensors present low accuracy in practical use because it is difficult to distinguish color changes for a minute amount of analyte with...

Intelligent personalized shopping recommendation using clustering and supervised machine learning algorithms.

PloS one
Next basket recommendation is a critical task in market basket data analysis. It is particularly important in grocery shopping, where grocery lists are an essential part of shopping habits of many customers. In this work, we first present a new groce...

Reliable prediction of cannabinoid receptor 2 ligand by machine learning based on combined fingerprints.

Computers in biology and medicine
Cannabinoid receptors, as part of the family of the G protein-coupled receptors (GPCRs), are involved in various physiological functions. Its subtype cannabinoid receptor subtype 2 (CB2), mainly distributed in the periphery, is a crucial therapeutic ...

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity.

Journal of chemical information and modeling
Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always requ...

Incremental Deep Neural Network Learning Using Classification Confidence Thresholding.

IEEE transactions on neural networks and learning systems
Most modern neural networks for classification fail to take into account the concept of the unknown. Trained neural networks are usually tested in an unrealistic scenario with only examples from a closed set of known classes. In an attempt to develop...

The Application of Deep Learning for the Evaluation of User Interfaces.

Sensors (Basel, Switzerland)
In this study, we tested the ability of a machine-learning model (ML) to evaluate different user interface designs within the defined boundaries of some given software. Our approach used ML to automatically evaluate existing and new web application d...

Evaluation of Machine Learning Techniques for Traffic Flow-Based Intrusion Detection.

Sensors (Basel, Switzerland)
Cybersecurity is one of the great challenges of today's world. Rapid technological development has allowed society to prosper and improve the quality of life and the world is more dependent on new technologies. Managing security risks quickly and eff...