scispace - formally typeset
Open AccessJournal ArticleDOI

Big data: Some statistical issues.

Reads0
Chats0
TLDR
A broad review is given of the impact of big data on various aspects of investigation and there is some but not total emphasis on issues in epidemiological research.
About
This article is published in Statistics & Probability Letters.The article was published on 2018-05-01 and is currently open access. It has received 48 citations till now.

read more

Citations
More filters
Journal ArticleDOI

A Structure-Based Drug Discovery Paradigm.

TL;DR: This review focuses on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.
Journal ArticleDOI

A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources

TL;DR: This work popularizes RF and their variants for the practicing water scientist, and discusses related concepts and techniques, which have received less attention from the water science and hydrologic communities.
Book ChapterDOI

Computational Drug Design Methods—Current and Future Perspectives

TL;DR: This chapter discusses the authors’ point of view of the challenges of traditional and novel CADD methods to increase their positive impact in drug discovery and presents emerging concepts and technologies in molecular modeling and chemoinformatics.
Journal ArticleDOI

Big spatial data for urban and environmental sustainability

TL;DR: This paper introduces four case studies and provides evidence that integrated methods can harness the advantages of both traditional data and BSD and improve the effectiveness of big data itself.
Journal ArticleDOI

The exposome - a new approach for risk assessment.

TL;DR: With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure and health/environment effect associations and may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an expo-sure-driven approach.
References
More filters
Journal ArticleDOI

Regression Shrinkage and Selection via the Lasso

TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Journal ArticleDOI

Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

Georges Aad, +2967 more
- 17 Sep 2012 - 
TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.
Journal ArticleDOI

Data Resource Profile: Clinical Practice Research Datalink (CPRD)

TL;DR: The CPRD primary care database is a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care, but researchers must be aware of the complexity of routinely collected electronic health records.
Journal ArticleDOI

Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available

TL;DR: This work outlines a framework for comparative effectiveness research using big data that makes the target trial explicit and channels counterfactual theory for comparing the effects of sustained treatment strategies, organizes analytic approaches, provides a structured process for the criticism of observational studies, and helps avoid common methodologic pitfalls.
Journal ArticleDOI

High-dimensional propensity score adjustment in studies of treatment effects using health care claims data

TL;DR: In typical pharmacoepidemiologic studies, the proposed high-dimensional propensity score resulted in improved effect estimates compared with adjustment limited to predefined covariates, when benchmarked against results expected from randomized trials.
Related Papers (5)