AIMC Topic: Machine Learning

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Predicting Colorectal Cancer Using Residual Deep Learning with Nursing Care.

Contrast media & molecular imaging
Presently, colorectal cancer is the second most dangerous cancer; around 13% of people have been affected; and it requires an effective image analysis and earlier cancer prediction (IAECP) system for reducing the mortality rate. Here, the IAECP syste...

Technology Matters: Machine learning approaches to personalised child and adolescent mental health care.

Child and adolescent mental health
There has been much interest in the potential for machine learning and artificial intelligence to enhance health care. In this article, we discuss the potential applications of the technology to child and adolescent mental health services (CAMHS). We...

A Novel Framework for Generating Personalized Network Datasets for NIDS Based on Traffic Aggregation.

Sensors (Basel, Switzerland)
In this paper, we addressed the problem of dataset scarcity for the task of network intrusion detection. Our main contribution was to develop a framework that provides a complete process for generating network traffic datasets based on the aggregatio...

Interpretable instance disease prediction based on causal feature selection and effect analysis.

BMC medical informatics and decision making
BACKGROUND: In the big wave of artificial intelligence sweeping the world, machine learning has made great achievements in healthcare in the past few years, however, these methods are only based on correlation, not causation. The particularities of t...

Measuring national mood with music: using machine learning to construct a measure of national valence from audio data.

Behavior research methods
We propose a new measure of national valence based on the emotional content of a country's most popular songs. We first trained a machine learning model using 191 different audio features embedded within music and use this model to construct a long-r...

Examining the utility of nonlinear machine learning approaches versus linear regression for predicting body image outcomes: The U.S. Body Project I.

Body image
Most body image studies assess only linear relations between predictors and outcome variables, relying on techniques such as multiple Linear Regression. These predictor variables are often validated multi-item measures that aggregate individual items...

A Multilevel Transfer Learning Technique and LSTM Framework for Generating Medical Captions for Limited CT and DBT Images.

Journal of digital imaging
Medical image captioning has been recently attracting the attention of the medical community. Also, generating captions for images involving multiple organs is an even more challenging task. Therefore, any attempt toward such medical image captioning...

Applications of machine learning in routine laboratory medicine: Current state and future directions.

Clinical biochemistry
Machine learning is able to leverage large amounts of data to infer complex patterns that are otherwise beyond the capabilities of rule-based systems and human experts. Its application to laboratory medicine is particularly exciting, as laboratory te...

FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches.

IEEE transactions on visualization and computer graphics
The machine learning (ML) life cycle involves a series of iterative steps, from the effective gathering and preparation of the data-including complex feature engineering processes-to the presentation and improvement of results, with various algorithm...

Characterization of English Braille Patterns Using Automated Tools and RICA Based Feature Extraction Methods.

Sensors (Basel, Switzerland)
Braille is used as a mode of communication all over the world. Technological advancements are transforming the way Braille is read and written. This study developed an English Braille pattern identification system using robust machine learning techni...