AIMC Topic: Machine Learning

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Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records.

BMC medical informatics and decision making
BACKGROUND: A new learning-based patient similarity measurement was proposed to measure patients' similarity for heterogeneous electronic medical records (EMRs) data.

Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning.

BMC medical informatics and decision making
BACKGROUND: Eligibility criteria are the primary strategy for screening the target participants of a clinical trial. Automated classification of clinical trial eligibility criteria text by using machine learning methods improves recruitment efficienc...

Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides (AMPs) are oligopeptides that act as crucial components of innate immunity, naturally occur in all multicellular organisms, and are involved in the first line of defense function. Recent studies showed that AMPs per...

Body shape matters: Evidence from machine learning on body shape-income relationship.

PloS one
The association between physical appearance and income has been of central interest in social science. However, most previous studies often measured physical appearance using classical proxies from subjective opinions based on surveys. In this study,...

Applicability of machine learning techniques in food intake assessment: A systematic review.

Critical reviews in food science and nutrition
The evaluation of food intake is important in scientific research and clinical practice to understand the relationship between diet and health conditions of an individual or a population. Large volumes of data are generated daily in the health sector...

The Role of Artificial Intelligence and Machine Learning in Clinical Cardiac Electrophysiology.

The Canadian journal of cardiology
In recent years, numerous applications for artificial intelligence (AI) in cardiology have been found, due in part to large digitized data sets and the evolution of high-performance computing. In the discipline of cardiac electrophysiology (EP), a nu...

Developing a boosted decision tree regression prediction model as a sustainable tool for compressive strength of environmentally friendly concrete.

Environmental science and pollution research international
One of the most significant parameters in concrete design is compressive strength. Time and money could be saved if the compressive strength of concrete is accurately measured. In this study, two machine learning models, namely, boosted decision tree...

Application of a Poisson deep neural network model for the prediction of count data in genome-based prediction.

The plant genome
Genomic selection (GS) is revolutionizing conventional ways of developing new plants and animals. However, because it is a predictive methodology, GS strongly depends on statistical and machine learning to perform these predictions. For continuous ou...

Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Human brain mapping
Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level...

Simulation and machine learning modelling based comparative study of InAlGaN and AlGaN high electron mobility transistors for the detection of HER-2.

Analytical methods : advancing methods and applications
The detection of the cancer biomarker human epidermal growth factor receptor 2 (HER-2) has always been challenging at the early stages of cancer due to its very small presence. A systematic study of biosensors to achieve optimum sensitivity is of par...