ArticleBMC medicine2019
Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom.
Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ethical issues raised by artificial intelligence and big data in population health: a scoping review.Frontiers in sociology · 2025Pooled it
- Implementing AI innovation in radiology departments in the English NHS: a qualitative study on the experiences of professionals, patient groups and innovators.Frontiers in digital health · 2026Article
- Review
- Article
- A machine learning-based depression risk prediction model for healthy middle-aged and older adult people based on data from the China health and aging tracking study.Frontiers in public health · 2025Article
- Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education.Medical education online · 2024Review
- Leading with AI in critical care nursing: challenges, opportunities, and the human factor.BMC nursing · 2024Article
- Investigating awareness of artificial intelligence in healthcare among medical students and professionals in Pakistan: a cross-sectional study.Annals of medicine and surgery (2012) · 2024Article
- Scheduling of Remote Monitoring for Peritoneal Dialysis Patients.Journal of clinical medicine · 2024Article
- Applications of Big Data and AI-Driven Technologies in CADD (Computer-Aided Drug Design).Methods in molecular biology (Clifton, N.J.) · 2024Article
- Digital Transformation Led by Nurses and Nursing Managers' Priorities: A Qualitative Study.Journal of nursing management · 2024Article
- The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice.Journal of personalized medicine · 2023Article
- Synthetic Health Data Can Augment Community Research Efforts to Better Inform the Public During Emerging Pandemics.medRxiv : the preprint server for health sciences · 2023Article
- Artificial Intelligence-Based Opportunities in Liver Pathology-A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Use of Electronic Medical Records (EMR) in Gerontology: Benefits, Considerations and a Promising Future.Clinical interventions in aging · 2023Review
- Editorial: Artificial intelligence: applications in clinical medicine.Frontiers in medical technology · 2023Article
- Morphometric Integrated Classification Index: A Multisite Model-Based, Interpretable, Shareable and Evolvable Biomarker for Schizophrenia.Schizophrenia bulletin · 2022Article
- Artificial Intelligence in Biological Sciences.Life (Basel, Switzerland) · 2022Review
- Targeting cellular senescence to combat cancer and ageing.Molecular oncology · 2022Review
- Computer vision coaching microsurgical laboratory training: PRIME (Proficiency Index in Microsurgical Education) proof of concept.Neurosurgical review · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Big data, coupled with the use of advanced analytical approaches, such as artificial intelligence (AI), have the potential to improve medical outcomes and population health. Data that are routinely generated from, for example, electronic medical records and smart devices have become progressively easier and cheaper to collect, process, and analyze. In recent decades, this has prompted a substantial increase in biomedical research efforts outside traditional clinical trial settings. Despite the apparent enthusiasm of researchers, funders, and the media, evidence is scarce for successful implementation of products, algorithms, and services arising that make a real difference to clinical care. This article collection provides concrete examples of how "big data" can be used to advance healthcare and discusses some of the limitations and challenges encountered with this type of research. It primarily focuses on real-world data, such as electronic medical records and genomic medicine, considers new developments in AI and digital health, and discusses ethical considerations and issues related to data sharing. Overall, we remain positive that big data studies and associated new technologies will continue to guide novel, exciting research that will ultimately improve healthcare and medicine-but we are also realistic that concerns remain about privacy, equity, security, and benefit to all.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.