ArticleFrontiers in medicine2020
Artificial Intelligence in Medicine: Today and Tomorrow.
Article in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05348109 (Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm), which is not on this map. Cited by 235 papers, 6 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.
Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm
Who cites it
235 citing papers in PubMed, 6 syntheses or guidelines pooled it, 645 citations in OpenAlex.
- Diagnostic accuracy of AI-assisted versus independent physician interpretation for bone fractures: a systematic review and meta-analysis.European radiology experimental · 2026Pooled it
- The transformative power of mHealth apps: empowering patients with obesity and diabetes - a narrative review.Journal of medicine and life · 2024Pooled it
- A systematic review of data sources for artificial intelligence applications in pediatric brain tumors in Europe: implications for bias and generalizability.Frontiers in oncology · 2023Pooled it
- Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications: A systematic review of the literature.Journal of nursing management · 2022Pooled it
- OMOP CDM Can Facilitate Data-Driven Studies for Cancer Prediction: A Systematic Review.International journal of molecular sciences · 2022Pooled it
- Artificial Intelligence in Bariatric Surgery: Current Status and Future Perspectives.Obesity surgery · 2022Pooled it
- Application of Artificial Intelligence and Machine Learning in Arrhythmia Detection and Pacemaker Data Analysis.Cardiology research · 2026Review
- Patient-governed agentic health data exchange.npj health systems · 2026Review
- Precision Prevention for Health: The Global Alliance Framework for the Promotion of Physical Activity.Sports medicine (Auckland, N.Z.) · 2026Article
- Challenges and Recommendations in Regulating AI Medical Devices in the European Union: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Social Health: A Narrative Review of Uses, Advantages, Challenges, and Future Directions.Healthcare (Basel, Switzerland) · 2026Review
- AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Wavelet-enhanced spatiotemporal connectivity-preserving network for intracranial artery segmentation in DSA sequences.Scientific reports · 2026Article
- AI-PACE: a framework for integrating AI into medical education.NPJ digital medicine · 2026Review
- Article
- Review
- Artificial Intelligence Algorithm Based on Genetics to Predict Responses to Interferon-Beta Treatment in Multiple Sclerosis Patients.Bioengineering (Basel, Switzerland) · 2026Article
- Improving Diabetic Foot Care With Infrared Thermography and Artificial Intelligence: A Review.Journal of diabetes science and technology · 2026Review
- Insights from deep learning models on new-onset anxiety in patients following bariatric metabolic surgery.Journal of affective disorders reports · 2026Article
- Leveraging ICT Tools to Improve Kidney Health: A Comprehensive Review of Innovations in Nephrology.Healthcare (Basel, Switzerland) · 2026Review
175 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence-powered medical technologies are rapidly evolving into applicable solutions for clinical practice. Deep learning algorithms can deal with increasing amounts of data provided by wearables, smartphones, and other mobile monitoring sensors in different areas of medicine. Currently, only very specific settings in clinical practice benefit from the application of artificial intelligence, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging. The implementation of augmented medicine is long-awaited by patients because it allows for a greater autonomy and a more personalized treatment, however, it is met with resistance from physicians which were not prepared for such an evolution of clinical practice. This phenomenon also creates the need to validate these modern tools with traditional clinical trials, debate the educational upgrade of the medical curriculum in light of digital medicine as well as ethical consideration of the ongoing connected monitoring. The aim of this paper is to discuss recent scientific literature and provide a perspective on the benefits, future opportunities and risks of established artificial intelligence applications in clinical practice on physicians, healthcare institutions, medical education, and bioethics.
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.