ReviewFrontiers in digital health2024
Prospects for AI clinical summarization to reduce the burden of patient chart review.
Review in Frontiers in digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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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
17 citing papers in PubMed.
- Artificial intelligence as cognitive support in emergency medicine.Clinical and experimental emergency medicine · 2026Article
- Conversational AI should fill the white space in mental health care, not replace humans.NPJ digital medicine · 2026Review
- Intelligent Automation Improved Efficiency in Pharmacovigilance Safety Signal Assessment.Clinical pharmacology and therapeutics · 2026Article
- Quality of Clinical Notes Created by Ambient Listening Generative AI: Pragmatic Prospective Pilot Study.JMIR medical informatics · 2026Article
- Cross-cancer survival prediction using machine learning models.Scientific reports · 2026Article
- Wolf Creek XVIII Part 5: cardiac arrest survivorship science.Resuscitation plus · 2026Article
- Cross-Institutional Evaluation of Large Language Models for Radiology Diagnosis Extraction: A Prompt-Engineering Perspective.Journal of imaging informatics in medicine · 2026Article
- Evaluation of electronic health record-integrated artificial intelligence chart review.npj health systems · 2026Article
- Simulation-Based Evaluation of a Large Language Model-Enabled Clinical Decision Support Platform in Oncology.JCO clinical cancer informatics · 2026Article
- The Infectious Diseases Orchestrator: Embracing AI Literacy in the Agentic Era.Open forum infectious diseases · 2026Article
- Article
- A framework for generative AI-driven extraction of clinical user needs in pediatric device development.Frontiers in digital health · 2026Article
- Ethical considerations of artificial intelligence in emergency medicine for triage and resource allocation: a scoping review.Clinical and experimental emergency medicine · 2025Article
- OphthoACR (Ophthalmology Automated Chart Review): An AI-Powered Tool for Complete Automation of Ophthalmology Chart Reviews and Cohort Data Analysis.Translational vision science & technology · 2025Article
- Artificial intelligence-generated encounter summaries: early insights from ambulatory clinicians at a large academic health system.JAMIA open · 2025Article
- Performance Evaluation of 18 Generative AI Models (ChatGPT, Gemini, Claude, and Perplexity) in 2024 Japanese Pharmacist Licensing Examination: Comparative Study.JMIR medical education · 2025Article
- Democratizing cost-effective, agentic artificial intelligence to multilingual medical summarization through knowledge distillation.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective summarization of unstructured patient data in electronic health records (EHRs) is crucial for accurate diagnosis and efficient patient care, yet clinicians often struggle with information overload and time constraints. This review dives into recent literature and case studies on both the significant impacts and outstanding issues of patient chart review on communications, diagnostics, and management. It also discusses recent efforts to integrate artificial intelligence (AI) into clinical summarization tasks, and its transformative impact on the clinician's potential, including but not limited to reductions of administrative burden and improved patient-centered care. Furthermore, it takes into account the numerous ethical challenges associated with integrating AI into clinical workflow, including biases, data privacy, and cybersecurity.
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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.