AIMC Topic: Machine Learning

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Machine learning-based analysis of adolescent gambling factors.

Journal of behavioral addictions
BACKGROUND AND AIMS: Problem gambling among adolescents has recently attracted attention because of easy access to gambling in online environments and its serious effects on adolescent lives. We proposed a machine learning-based analysis method for p...

Recent advances on the machine learning methods in predicting ncRNA-protein interactions.

Molecular genetics and genomics : MGG
Recent transcriptomics and bioinformatics studies have shown that ncRNAs can affect chromosome structure and gene transcription, participate in the epigenetic regulation, and take part in diseases such as tumorigenesis. Biologists have found that mos...

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms.

Scientific reports
Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging...

Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences.

BMC medical informatics and decision making
BACKGROUND: Computer Aided Diagnostics (CAD) can support medical practitioners to make critical decisions about their patients' disease conditions. Practitioners require access to the chain of reasoning behind CAD to build trust in the CAD advice and...

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.

BMC medical informatics and decision making
BACKGROUND: Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs) make optimal clinical decisions. This study aimed to develop machine learning-based tools to predi...

Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data.

BMC medical informatics and decision making
BACKGROUND: With cardiovascular disease increasing, substantial research has focused on the development of prediction tools. We compare deep learning and machine learning models to a baseline logistic regression using only 'known' risk factors in pre...

Identification of Risk Factors and Symptoms of COVID-19: Analysis of Biomedical Literature and Social Media Data.

Journal of medical Internet research
BACKGROUND: In December 2019, the COVID-19 outbreak started in China and rapidly spread around the world. Lack of a vaccine or optimized intervention raised the importance of characterizing risk factors and symptoms for the early identification and s...

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts.

European radiology
In recent years, there has been a dramatic increase in research papers about machine learning (ML) and artificial intelligence in radiology. With so many papers around, it is of paramount importance to make a proper scientific quality assessment as t...