ReviewCureus2025
The Evolving Role of Artificial Intelligence in Medical Science: Advancing Diagnostics, Clinical Decision-Making, and Research.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Effectiveness of an AI-augmented teacher feedback model in improving medical students' clinical documentation skills: a retrospective cohort study.BMC medical education · 2026Article
- Digital health in clinical pharmacy practice: transforming precision medicine and pharmacometrics in Africa.Frontiers in pharmacology · 2026Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is transforming medical science by advancing diagnostics, clinical decision-making, research, and healthcare management. Utilizing machine learning (ML) and deep learning, AI can analyze complex datasets, identify patterns, and generate accurate predictive insights. AI-powered imaging systems and Clinical Decision Support Systems (CDSS) support early disease detection and evidence-based treatment with accuracy comparable to expert clinicians. In medical research, AI accelerates drug discovery, genomic analysis, and clinical trial optimization by mining large datasets for therapeutic targets. In healthcare management, AI enhances resource allocation, streamlines hospital operations, and improves patient interaction through virtual assistants and telemedicine. Despite these advancements, several challenges persist, including concerns about data privacy, algorithmic bias, lack of transparency in AI models, and limited physician acceptance. Ethical integration requires explainable AI, strong regulatory frameworks, and interdisciplinary collaboration. As the field evolves, AI holds great promise in precision medicine, robotic-assisted surgery, and medical education. It is also offering personalized treatment, improved surgical outcomes, and adaptive learning tools for students. Therefore, realizing this potential depends on building trust among healthcare professionals, validating AI systems, and addressing disparities in access, especially in underserved regions. AI can reshape healthcare into a more accurate, efficient, and patient-centered system worldwide with thoughtful implementation and continued innovation.
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.