ArticleScientific reports2022
Experimental evidence of effective human-AI collaboration in medical decision-making.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.
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Who cites it
56 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Computer-aided diagnosis for colorectal polyp in comparison with endoscopists: Systematic review and meta-analysis.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2025Pooled it
- When combinations of humans and AI are useful: A systematic review and meta-analysis.Nature human behaviour · 2024Pooled it
- GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial.Nature medicine · 2025Trial
- Electronic Health Record Workflows in Acute Care Surgery: Ethnographic Study.JMIR medical informatics · 2026Article
- Factors Associated With Professionals' Context-Specific Trust in AI-Based Screening for Autism Spectrum Disorder: Cross-Sectional Survey Study.JMIR formative research · 2026Article
- Performance of large language models in ambiguous treatment scenarios of early breast cancer.Breast (Edinburgh, Scotland) · 2026Article
- Intelligent Automation Improved Efficiency in Pharmacovigilance Safety Signal Assessment.Clinical pharmacology and therapeutics · 2026Article
- Benchmarking large language models against practicing clinicians on psychopathological assessment.NPJ digital medicine · 2026Article
- A scoping review of human-AI collaboration patterns and task divisions in healthcare applications.NPJ digital medicine · 2026Article
- Do AI-based contouring algorithms influence physicians in the online adaptive radiotherapy of patients with bladder cancer?Technical innovations & patient support in radiation oncology · 2026Article
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- Adaptive yet suboptimal integration of advice in decision-making.Communications psychology · 2026Article
- Warning people about the risk of AI error mitigates human acquisition of AI bias.Cognitive research: principles and implications · 2026Article
- Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisions.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2026Article
- Article
- Screenathon 2.0: human-AI collaborative screening applied to patient-generated health data.Scientific reports · 2026Article
- IsAI & society · 2026Article
- Structured Integration of an Artificial Intelligence-Based System for the Optical Diagnosis of Colorectal Polyps.Gut and liver · 2026Article
- Virtual medicine: medical AI in human health and diseases.Military Medical Research · 2026Review
- Nurse-led digital triage and health literacy navigation: redefining the front door of public health in the artificial intelligence era.Frontiers in public health · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) systems are precious support for decision-making, with many applications also in the medical domain. The interaction between MDs and AI enjoys a renewed interest following the increased possibilities of deep learning devices. However, we still have limited evidence-based knowledge of the context, design, and psychological mechanisms that craft an optimal human-AI collaboration. In this multicentric study, 21 endoscopists reviewed 504 videos of lesions prospectively acquired from real colonoscopies. They were asked to provide an optical diagnosis with and without the assistance of an AI support system. Endoscopists were influenced by AI ([Formula: see text]), but not erratically: they followed the AI advice more when it was correct ([Formula: see text]) than incorrect ([Formula: see text]). Endoscopists achieved this outcome through a weighted integration of their and the AI opinions, considering the case-by-case estimations of the two reliabilities. This Bayesian-like rational behavior allowed the human-AI hybrid team to outperform both agents taken alone. We discuss the features of the human-AI interaction that determined this favorable outcome.
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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.