AIMC Topic: Big Data

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Public Medical Appeals and Government Online Responses: Big Data Analysis Based on Chinese Digital Governance Platforms.

Journal of medical Internet research
BACKGROUND: In the era of internet-based governance, online public appeals-particularly those related to health care-have emerged as a crucial channel through which citizens articulate their needs and concerns.

Nontarget Screening Analysis Combined with Computational Toxicology: A Promising Solution for Identification and Risk Assessment of Environmental Pollutants in the Big Data Era.

Environmental science & technology
Synthetic chemicals are intensively utilized in modern societies, and their mixtures pose significant health and ecological threats. Nontarget screening (NTS) analysis allows for the simultaneous chemical identification and quantitative reporting of ...

Event-Driven Taxonomy (EDT) Screening: Leveraging Effect-Based Spectral Libraries to Accelerate Semiquantitative Nontarget Analysis of AhR Agonists in Sediment in the Era of Big Data.

Environmental science & technology
Sediments contain complex chemical mixtures. While effect-directed analysis (EDA) combined with nontarget screening (NTS) is promising, its large-scale application has been limited by time-consuming workflows. Here, we developed an event-driven taxon...

Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data.

PloS one
BACKGROUND: Road traffic accidents (RTAs) are a major public health concern with significant health and economic burdens. Identifying high-risk areas and key contributing factors is essential for developing targeted interventions. While machine learn...

A big data driven multilevel deep learning framework for predicting terrorist attacks.

Scientific reports
In recent years, terrorism has increasingly threatened human security, causing violence, fear, and damage to both the general public and specific targets. These attacks create unrest among individuals and within society. Leveraging the recent advance...

Journal of Global Health's Guidelines for Reporting Analyses of Big Data Repositories Open to the Public (GRABDROP): preventing 'paper mills', duplicate publications, misuse of statistical inference, and inappropriate use of artificial intelligence.

Journal of global health
In recent years, global accessibility to large 'big data' repositories that enable 'open research' - such as the UK Biobank, National Health and Nutrition Examination Survey (NHANES), and Global Burden of Disease (GBD) datasets - has created unpreced...

The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review.

JMIR medical informatics
BACKGROUND: Machine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. With the increasing availability of real-world data (RWD) from diverse sources, such as...

The analysis of marketing performance in E-commerce live broadcast platform based on big data and deep learning.

Scientific reports
This study aims to conduct a comprehensive and in-depth analysis of the marketing performance of e-commerce live broadcast platforms based on big data management technology and deep learning. Firstly, by synthesizing large-scale datasets and surveys,...

Are Treatment Services Ready for the Use of Big Data Analytics and AI in Managing Opioid Use Disorder?

Journal of medical Internet research
In this viewpoint, we explore the use of big data analytics and artificial intelligence (AI) and discuss important challenges to their ethical, effective, and equitable use within opioid use disorder (OUD) treatment settings. Applying our collective ...

Big data-driven target identification by machine learning: DRD2 as a therapeutic target for psoriasis.

Journal of dermatological science
BACKGROUND: The development of medical treatments has traditionally relied on researchers leveraging scientific knowledge to hypothesize disease mechanisms and identify therapeutic agents. However, the depletion of novel therapeutic targets has becom...