AIMC Topic: Machine Learning

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ME-Class2 reveals context dependent regulatory roles for 5-hydroxymethylcytosine.

Nucleic acids research
Since the discovery of 5-hydroxymethylcytosine (5hmC) as a prominent DNA modification found in mammalian genomes, an emergent question has been what role this mark plays in gene regulation. 5hmC is hypothesized to function as an intermediate in the d...

Discovery of Distinct Immune Phenotypes Using Machine Learning in Pulmonary Arterial Hypertension.

Circulation research
RATIONALE: Accumulating evidence implicates inflammation in pulmonary arterial hypertension (PAH) and therapies targeting immunity are under investigation, although it remains unknown if distinct immune phenotypes exist.

miES: predicting the essentiality of miRNAs with machine learning and sequence features.

Bioinformatics (Oxford, England)
MOTIVATION: MicroRNAs (miRNAs) are one class of small noncoding RNA molecules, which regulate gene expression at the post-transcriptional level and play important roles in health and disease. To dissect the critical miRNAs in miRNAome, it is needed t...

Medical assertion classification in Chinese EMRs using attention enhanced neural network.

Mathematical biosciences and engineering : MBE
Electronic medical records (EMRs), such as hospital discharge summaries, contain a wealth of information only expressed in natural language. Automated methods for extracting information from these records must be able to recognize medical concepts in...

Recurrent Neural Networks in Mobile Sampling and Intervention.

Schizophrenia bulletin
The rapid rise and now widespread distribution of handheld and wearable devices, such as smartphones, fitness trackers, or smartwatches, has opened a new universe of possibilities for monitoring emotion and cognition in everyday-life context, and for...

Determinants of In-Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach.

Journal of the American Heart Association
Background The ability to accurately predict the occurrence of in-hospital death after percutaneous coronary intervention is important for clinical decision-making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System...

Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.

Journal of the American Heart Association
Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learning technique called Bayesian Additive Regression Trees ( BART ). Methods and Results This analysis included 4714 participants from MESA (Multi-Ethnic S...

Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets.

IEEE transactions on medical imaging
In this paper, we developed a deep convolutional neural network (CNN) for the classification of malignant and benign masses in digital breast tomosynthesis (DBT) using a multi-stage transfer learning approach that utilized data from similar auxiliary...

Machine Learning as an Effective Method for Identifying True Single Nucleotide Polymorphisms in Polyploid Plants.

The plant genome
Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid species is difficult. Peanut ( L.) is an allopolyploid, which has a very low r...