AIMC Topic: Data Science
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Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap.
Clinical pharmacology and therapeutics
Jan 22, 2020
Despite the application of advanced statistical and pharmacometric approaches to pediatric trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more data from children by using real-world data from electronic heal...
In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics.
Nature communications
Jan 9, 2020
Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent acquisition (DDA) experiments are required prior to DIA ...
Supervised and unsupervised algorithms for bioinformatics and data science.
Progress in biophysics and molecular biology
Dec 6, 2019
Bioinformatics refers to an ever evolving huge field of research based on millions of algorithms, designated to several data banks. Such algorithms are either supervised or unsupervised. In this article, a detailed overview of the supervised and unsu...
Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.
Bipolar disorders
Sep 18, 2019
OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learnin...
Data science in modern evidence-based medicine.
Journal of the Royal Society of Medicine
Sep 17, 2019
Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets.
Neural networks : the official journal of the International Neural Network Society
Aug 1, 2019
A data augmentation methodology is presented and applied to generate a large dataset of off-axis iris regions and train a low-complexity deep neural network. Although of low complexity the resulting network achieves a high level of accuracy in iris r...
Artificial intelligence in dermato-oncology: a joint clinical and data science perspective.
International journal of dermatology
May 31, 2019
Uncovering the structure of self-regulation through data-driven ontology discovery.
Nature communications
May 24, 2019
Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issue...
Intelligent health data analytics: A convergence of artificial intelligence and big data.
Healthcare management forum
May 22, 2019
Healthcare is a living system that generates a significant volume of heterogeneous data. As healthcare systems are pivoting to value-based systems, intelligent and interactive analysis of health data is gaining significance for health system manageme...
Data science, artificial intelligence, and machine learning: Opportunities for laboratory medicine and the value of positive regulation.
Clinical biochemistry
Apr 22, 2019
Artificial intelligence (AI) and data science are rapidly developing in healthcare, as is their translation into laboratory medicine. Our review article presents an overview of the data science domain while discussing the reasons for its emergence. W...
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