AIMC Topic: Data Mining

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Literature mining for context-specific molecular relations using multimodal representations (COMMODAR).

BMC bioinformatics
Biological contextual information helps understand various phenomena occurring in the biological systems consisting of complex molecular relations. The construction of context-specific relational resources vastly relies on laborious manual extraction...

Potentials and caveats of AI in hybrid imaging.

Methods (San Diego, Calif.)
State-of-the-art patient management frequently mandates the investigation of both anatomy and physiology of the patients. Hybrid imaging modalities such as the PET/MRI, PET/CT and SPECT/CT have the ability to provide both structural and functional in...

Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Nontraumatic intracranial hemorrhage (ICH) is a neurological emergency of research interest; however, unlike ischemic stroke, has not been well studied in large datasets due to the lack of an established administrative claims-based defi...

Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples.

BMC medical research methodology
BACKGROUND: Unstructured data from clinical epidemiological studies can be valuable and easy to obtain. However, it requires further extraction and processing for data analysis. Doing this manually is labor-intensive, slow and subject to error. In th...

Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing.

Methods of information in medicine
BACKGROUND: Merging disparate and heterogeneous datasets from clinical routine in a standardized and semantically enriched format to enable a multiple use of data also means incorporating unstructured data such as medical free texts. Although the ext...

Statistical and Machine-Learning Analyses in Nutritional Genomics Studies.

Nutrients
Nutritional compounds may have an influence on different OMICs levels, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and metagenomics. The integration of OMICs data is challenging but may provide new knowledge to explain...

Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease.

Circulation. Cardiovascular interventions
BACKGROUND: Peripheral artery disease (PAD) is underrecognized, undertreated, and understudied: each of these endeavors requires efficient and accurate identification of patients with PAD. Currently, PAD patient identification relies on diagnosis/pro...

Data mining of human plasma proteins generates a multitude of highly predictive aging clocks that reflect different aspects of aging.

Aging cell
We previously identified 529 proteins that had been reported by multiple different studies to change their expression level with age in human plasma. In the present study, we measured the q-value and age coefficient of these proteins in a plasma prot...

An embedded gene selection method using knockoffs optimizing neural network.

BMC bioinformatics
BACKGROUND: Gene selection refers to find a small subset of discriminant genes from the gene expression profiles. How to select genes that affect specific phenotypic traits effectively is an important research work in the field of biology. The neural...

Data-driven ICU management: Using Big Data and algorithms to improve outcomes.

Journal of critical care
The digitalization of the Intensive Care Unit (ICU) led to an increasing amount of clinical data being collected at the bedside. The term "Big Data" can be used to refer to the analysis of these datasets that collect enormous amount of data of differ...