ReviewMedicine and pharmacy reports2024
Artificial Intelligence and medical specialties: support or substitution?
Review in Medicine and pharmacy reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis 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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Laryngeal Cancer Detection: A Systematic Review and Meta-Analysis.Current oncology (Toronto, Ont.) · 2025Pooled it
- Comparing the text-based diagnostic reasoning performance of emergency medicine physicians and large language models in both definitive and differential diagnoses using standardized clinical vignettes: a preliminary study.International journal of emergency medicine · 2026Article
- Experiences and Perceptions of Clinical and Graduate Medical Students Regarding AI in Syria: Cross-Sectional Study.JMIR medical education · 2026Article
- What drives Malaysian medical students' specialty choices? Findings from the MMSCI study.Human resources for health · 2025Article
- AI-Augmented Fundus Disease Screening by Non-Ophthalmologist Physicians: A Paired Before-After Study.Bioengineering (Basel, Switzerland) · 2025Article
- Mathematical and AI-Based Predictive Modelling for Dental Caries Risk Using Clinical and Behavioural Parameters.Bioengineering (Basel, Switzerland) · 2025Article
- Optimizing Cancer Treatment: Exploring the Role of AI in Radioimmunotherapy.Diagnostics (Basel, Switzerland) · 2025Review
- Artificial Intelligence in Dentistry: A Descriptive Review.Bioengineering (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid advancement of artificial intelligence (AI) in healthcare has spurred extensive debate regarding its potential to replace human expertise across various medical specialties. This narrative review critically examines the integration of AI within diverse medical specialties to discern its role as a substitute or supporter. The analysis encompasses AI's impact on diagnostic precision, treatment planning, and patient care. Although AI systems have demonstrated remarkable proficiency in tasks reliant on data analysis and pattern recognition, they fall short in areas necessitating nuanced decision-making, empathetic communication, and the application of human medical expertise in diagnosis and treatment planning. The rapid evolution of AI applications within medical specialties is propelled by the swift advancements in both hardware and software technologies, fostering a dynamic synergy that continues to redefine the boundaries of precision and efficiency in healthcare delivery. While AI demonstrates remarkable capabilities in automating tasks, it is underscored that its integration in complex domains necessitates a balanced approach that preserves the indispensable contributions of human activity.
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.