ReviewCureus2024
Artificial Intelligence in Healthcare With an Emphasis on Public Health.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- "First, do no harm" in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence: A systematic literature review.BMC medical ethics · 2026Pooled it
- Feasibility of AI-driven disease surveillance systems at international airports in sub-Saharan Africa: a narrative review.Frontiers in public health · 2026Review
- Global status of policies and practices for systematic TB screening in high-burden countries.IJTLD open · 2025Article
- Review
- Harnessing artificial intelligence for enhanced public health surveillance: a narrative review.Frontiers in public health · 2025Review
- Telemedicine: the Technological Revolution to Address Healthcare System Shortcomings.Journal of preventive medicine and hygiene · 2024Article
- Harnessing artificial intelligence and digital technology for enhancing routine immunization among zero-dose children.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI), since its inception, has revolutionized multiple sectors, including healthcare in the 20th century, and has applications in data interpretation, leading to advancements in diagnostics, therapeutics, and clinical decision-making. AI is referred to as the capability of a software program to accurately analyze extrinsic information and utilize it for accomplishing desired goals and objectives through appropriate flexibility. It makes use of complicated operative algorithms to excel in human learning potential with overwhelming abilities to interpret large sets of data. The scope and implications of AI are consistently amplifying and have contributed significantly in nearly all phases of human life, especially healthcare. The integration of AI-related advancements would surely ameliorate the delivery of healthcare by allowing its accessibility, affordability, and level of care provided. For instance, reading CT scans is feasible by both AI as well as a radiologist. The screening of Tuberculosis is possible through AI via Chest X-rays with comparability in performance as molecular testing and mammography scans can predict the onset of breast cancer prior to the appearance of the ocular signs. Therefore, AI has been realized as one of the core areas by researchers and the government for public health benefit. For the same reason, it is imperative to adopt an ethically sound policy framework for guiding the further development of AI-based technologies and their application in public health. AI-based interpretations themselves cannot be fully trusted for their diagnostic decisions and judgements, and hence, it is vital to assess their accountability through all phases of development and deployment in the field of health. This article emphasizes the advancements in AI-based technologies, their assistance in public healthcare delivery systems, and their merits and demerits. It also explores the various ethical directives that need to be adhered to while utilizing it for public health welfare.
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.