ReviewFrontiers in artificial intelligence2021
What Makes Artificial Intelligence Exceptional in Health Technology Assessment?
Review in Frontiers in artificial intelligence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses 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
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Nurses' Experiences Using AI in Clinical Practice: Systematic Review.JMIR nursing · 2026Pooled it
- Ethical issues raised by artificial intelligence and big data in population health: a scoping review.Frontiers in sociology · 2025Pooled it
- Ethical Considerations in Health Technology Assessment for Precision Medicine: A Delphi Study in a Greek Setting.Journal of personalized medicine · 2026Article
- Exploring the challenges of developing hospital-based health technology assessment in Iran: a qualitative study.Health research policy and systems · 2026Article
- Integrating ethical analysis in health technology assessment: opportunities and challenges.International journal of technology assessment in health care · 2026Article
- Emerging shadow health systems: regulating health-focused generative AI chatbots from a European perspective.Frontiers in public health · 2026Article
- Promoting xenomorphic patient-facing AIs: The case against anthropomorphism in medical AIs.NPJ digital medicine · 2025Review
- It Is Not About AI, It's About Humans. Responsibility Gaps and Medical AI.Journal of bioethical inquiry · 2025Article
- Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy.Journal of medical systems · 2025Article
- Applications of artificial intelligence and the challenges in health technology assessment: a scoping review and framework with a focus on economic dimensions.Health economics review · 2025Review
- ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment-practice recommendations by the European Society of Medical Imaging Informatics.European radiology · 2025Review
- Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges.BMC cancer · 2025Article
- Health technology assessment framework for artificial intelligence-based technologies.International journal of technology assessment in health care · 2024Article
- Is health technology assessment ready for generative pretrained transformer large language models? Report of a fishbowl inquiry.International journal of technology assessment in health care · 2024Review
- How should we train clinicians for artificial intelligence in healthcare?Future healthcare journal · 2024Article
- Suitability of the Current Health Technology Assessment of Innovative Artificial Intelligence-Based Medical Devices: Scoping Literature Review.Journal of medical Internet research · 2024Article
- Artificial Intelligence to Automate Health Economic Modelling: A Case Study to Evaluate the Potential Application of Large Language Models.PharmacoEconomics - open · 2024Article
- Ethics dumping in artificial intelligence.Frontiers in artificial intelligence · 2024Article
- Why we need to be careful with LLMs in medicine.Frontiers in medicine · 2024Article
- The ethics of artificial intelligence use in university libraries in Zimbabwe.Frontiers in research metrics and analytics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of artificial intelligence (AI) may revolutionize the healthcare system, leading to enhance efficiency by automatizing routine tasks and decreasing health-related costs, broadening access to healthcare delivery, targeting more precisely patient needs, and assisting clinicians in their decision-making. For these benefits to materialize, governments and health authorities must regulate AI, and conduct appropriate health technology assessment (HTA). Many authors have highlighted that AI health technologies (AIHT) challenge traditional evaluation and regulatory processes. To inform and support HTA organizations and regulators in adapting their processes to AIHTs, we conducted a systematic review of the literature on the challenges posed by AIHTs in HTA and health regulation. Our research question was: What makes artificial intelligence exceptional in HTA? The current body of literature appears to portray AIHTs as being exceptional to HTA. This exceptionalism is expressed along 5 dimensions: 1) AIHT's distinctive features; 2) their systemic impacts on health care and the health sector; 3) the increased expectations towards AI in health; 4) the new ethical, social and legal challenges that arise from deploying AI in the health sector; and 5) the new evaluative constraints that AI poses to HTA. Thus, AIHTs are perceived as exceptional because of their technological characteristics
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.