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Big Data

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Big data in severe mental illness: the role of electronic monitoring tools and metabolomics.

Personalized medicine
There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized ...

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses.

BMC bioinformatics
BACKGROUND: A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the Tree-based Pipeline Optimiza...

[Big Data, AI and Machine Learning for Precision Psychiatry: How are they changing the clinical practice?].

Fortschritte der Neurologie-Psychiatrie
Currently, we are witnessing an increasing interest in predictive models and personalized diagnosis and treatment choice in psychiatric research. Against this background, the emerging field of Precision Psychiatry is trying to establish precise diagn...

The Coming of Age for Big Data in Systems Radiobiology, an Engineering Perspective.

Big data
As high-throughput approaches in biological and biomedical research are transforming the life sciences into information-driven disciplines, modern analytics platforms for big data have started to address the needs for efficient and systematic data an...

Ensemble-based deep learning for estimating PM over California with multisource big data including wildfire smoke.

Environment international
INTRODUCTION: Estimating PM concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in nat...

The Emerging Role of Artificial Intelligence in the Fight Against COVID-19.

European urology
The coronavirus disease 2019 (COVID-19) pandemic has generated large volumes of clinical data that can be an invaluable resource towards answering a number of important questions for this and future pandemics. Artificial intelligence can have an impo...

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

Nature reviews. Nephrology
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medic...

Artificial intelligence in trauma systems.

Surgery
Local trauma care and regional trauma systems are data-rich environments that are amenable to machine learning, artificial intelligence, and big-data analysis mechanisms to improve timely access to care, to measure outcomes, and to improve quality of...

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...