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Biomedical Research

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Extracting Inter-Sentence Relations for Associating Biological Context with Events in Biomedical Texts.

IEEE/ACM transactions on computational biology and bioinformatics
We present an analysis of the problem of identifying biological context and associating it with biochemical events described in biomedical texts. This constitutes a non-trivial, inter-sentential relation extraction task. We focus on biological contex...

Extraction of the molecular level biomedical event trigger based on gene ontology using radial belief neural network techniques.

Bio Systems
Detection of molecular level biomedical event extraction plays a vital role in creating and visualizing the applications related to natural language processing. Cystic Fibrosis is an inherited genetic and debilitating pathology involving the respirat...

Accuracy of machine learning-based prediction of medication adherence in clinical research.

Psychiatry research
Medication non-adherence represents a significant barrier to treatment efficacy. Remote, real-time measurement of medication dosing can facilitate dynamic prediction of risk for medication non-adherence, which in-turn allows for proactive clinical in...

A data-driven dimensionality-reduction algorithm for the exploration of patterns in biomedical data.

Nature biomedical engineering
Dimensionality reduction is widely used in the visualization, compression, exploration and classification of data. Yet a generally applicable solution remains unavailable. Here, we report an accurate and broadly applicable data-driven algorithm for d...

Recommendations for Reporting Machine Learning Analyses in Clinical Research.

Circulation. Cardiovascular quality and outcomes
Use of machine learning (ML) in clinical research is growing steadily given the increasing availability of complex clinical data sets. ML presents important advantages in terms of predictive performance and identifying undiscovered subpopulations of ...

Deep learning in next-generation sequencing.

Drug discovery today
Next-generation sequencing (NGS) methods lie at the heart of large parts of biological and medical research. Their fundamental importance has created a continuously increasing demand for processing and analysis methods of the data sets produced, addr...

Deep transfer learning for reducing health care disparities arising from biomedical data inequality.

Nature communications
As artificial intelligence (AI) is increasingly applied to biomedical research and clinical decisions, developing unbiased AI models that work equally well for all ethnic groups is of crucial importance to health disparity prevention and reduction. H...

Application of BERT to Enable Gene Classification Based on Clinical Evidence.

BioMed research international
The identification of profiled cancer-related genes plays an essential role in cancer diagnosis and treatment. Based on literature research, the classification of genetic mutations continues to be done manually nowadays. Manual classification of gene...