ReviewCureus2023
Perspective of Artificial Intelligence in Disease Diagnosis: A Review of Current and Future Endeavours in the Medical Field.
Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed.
- AI Health Services and Health Satisfaction Across Socioeconomic Groups in South Korea: National Cross-Sectional Study Using an Instrumental Variable Approach.Journal of medical Internet research · 2026Article
- Article
- Artificial intelligence and radiomics in drug-induced interstitial lung disease.ERJ open research · 2026Review
- Artificial Intelligence For 6P Medicine: Consolidating AI Needs of Predictive, Preventive, Personalized, Participatory, Precision, and Public Health Trajectories.Journal of medical systems · 2026Review
- The Use of Artificial Intelligence in Improving Diagnostic Modalities in Rheumatoid Arthritis: A Narrative Review.Cureus · 2026Review
- Article
- Chemometric Methods Applied to Infrared and Raman Spectroscopy for Arboviruses Diagnosis: A Systematic Review With Meta-Analysis.Analytical science advances · 2025Review
- Artificial Intelligence in Australian Dental and General Healthcare: A Scoping Review.Australian dental journal · 2025Article
- Balancing Accuracy and Readability: Comparative Evaluation of AI Chatbots for Patient Education on Rotator Cuff Tears.Healthcare (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review.Medicina (Kaunas, Lithuania) · 2025Review
- Correlates of Medical and Allied Health Students' Engagement with Generative AI in Nigeria.Medical science educator · 2025Article
- HFSA: hybrid feature selection approach to improve medical diagnostic system.PeerJ. Computer science · 2025Article
- Assessing the effectiveness of machine learning and deep learning in differentiating neuroimmunological diseases: a systematic review and meta-analysis.Frontiers in neurology · 2025Article
- Diagnostic Challenges in Uncommon Firearm Injury Cases: A Multidisciplinary Approach.Diagnostics (Basel, Switzerland) · 2024Article
- Diagnosis Based on Population Data versus Personalized Data: The Evolving Paradigm in Laboratory Medicine.Diagnostics (Basel, Switzerland) · 2024Review
- Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research.JMIR medical education · 2024Article
- A Novel Automatic Algorithm to Support Lung Ultrasound Non-Expert Physicians in Interstitial Pneumonia Evaluation: A Single-Center Study.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial intelligence and machine learning for joint disorder detection: Promising advances in diagnostics.International journal of health sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has demonstrated significant promise for the present and future diagnosis of diseases. At the moment, AI-powered diagnostic technologies can help physicians decipher medical pictures like X-rays, magnetic resonance imaging, and computed tomography scans, resulting in quicker and more precise diagnoses. In order to make a prospective diagnosis, AI algorithms may also examine patient information, symptoms, and medical background. The application of AI in disease diagnosis is anticipated to grow as the field develops. In the future, AI may be used to find patterns in enormous volumes of medical data, aiding in disease prediction and prevention before symptoms appear. Additionally, by combining genetic data, lifestyle data, and environmental variables, AI may help in the diagnosis of complicated diseases. It is crucial to remember that while AI can be a powerful tool, it cannot take the place of qualified medical personnel. Instead, AI ought to support and improve diagnostic procedures, enhancing patient care and healthcare results. Future research and the use of AI for disease diagnosis must take ethical issues, data protection, and ongoing model validation into account.
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.