AIMC Topic: Machine Learning

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A comparison of regularized logistic regression and random forest machine learning models for daytime diagnosis of obstructive sleep apnea.

Medical & biological engineering & computing
A major challenge in big and high-dimensional data analysis is related to the classification and prediction of the variables of interest by characterizing the relationships between the characteristic factors and predictors. This study aims to assess ...

Evaluation of Hyperparameter Optimization in Machine and Deep Learning Methods for Decoding Imagined Speech EEG.

Sensors (Basel, Switzerland)
Classification of electroencephalography (EEG) signals corresponding to imagined speech production is important for the development of a direct-speech brain-computer interface (DS-BCI). Deep learning (DL) has been utilized with great success across s...

Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Twitter is a potentially valuable tool for public health officials and state Medicaid programs in the United States, which provide public health insurance to 72 million Americans.

Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models.

Journal of medical Internet research
BACKGROUND: The inherent difficulty of identifying and monitoring emerging outbreaks caused by novel pathogens can lead to their rapid spread; and if left unchecked, they may become major public health threats to the planet. The ongoing coronavirus d...

Learning machine approach reveals microbial signatures of diet and sex in dog.

PloS one
The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already inve...

A brief introduction to concepts and applications of artificial intelligence in dental imaging.

Oral radiology
This report aims to summarize the fundamental concepts of Artificial Intelligence (AI), and to provide a non-exhaustive overview of AI applications in dental imaging, comprising diagnostics, forensics, image processing and image reconstruction. AI ha...

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography.

Journal of visualized experiments : JoVE
Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translation...

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.

Journal of visualized experiments : JoVE
Machine learning (ML) algorithms permit the integration of different features into a model to perform classification or regression tasks with an accuracy exceeding its constituents. This protocol describes the development of an ML algorithm to predic...

Predicting In-Hospital Mortality at Admission to the Medical Ward: A Big-Data Machine Learning Model.

The American journal of medicine
BACKGROUND: General medical wards admit high-risk patients. Artificial intelligence algorithms can use big data for developing models to assess patients' risk stratification. The aim of this study was to develop a mortality prediction machine learnin...

A data-driven approach to build a predictive model of cancer patients' disease outcome by utilizing co-expression networks.

Computers in biology and medicine
BACKGROUND: Next Generation Sequencing (NGS) technologies have revolutionized genomics data research over the last decades by facilitating high-throughput sequencing of genetic material such as RNA Sequencing (RNAseq). A significant challenge is to e...