ArticleEJIFCC2025
Tribulations, Triumphs, and Governance: Shaping the Future of Artificial Intelligence in Healthcare.
Article in EJIFCC, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is driving a profound transformation across the healthcare landscape, with the potential to enhance diagnostic accuracy, optimize clinical decision-making, improve resource allocation, and advance personalized medicine. In public health, AI is redefining infectious disease epidemiology by enabling outbreak forecasting, genomic surveillance, and data-driven policy support, even in the presence of incomplete information. Within clinical laboratories, AI plays a pivotal and expanding role. It facilitates automation of complex workflows, supports diagnostic interpretation, and contributes to analytical performance improvements. Particularly promising is its integration into point-of-care testing, enabling decentralized diagnostics and broader access to timely care, especially in resource-constrained settings. However, these advancements are not without challenges. Concerns regarding algorithmic bias, lack of data representativeness, and risks to privacy and transparency must be carefully addressed. Moreover, the ethical and societal implications of AI are increasingly central. As emphasized by Pope Francis, while AI may accelerate access to knowledge and innovation, it also risks deepening global disparities and promoting a "throwaway culture" that undermines human dignity. His appeal for a "culture of encounter" rooted in equity, justice, and inclusion aligns with the mission of public health and laboratory medicine. This paper, based on the invited lecture delivered at the Clinical Laboratories Artificial Intelligence Revolution (CLAIR) 2025 conference, explores these themes through a critical lens. International scientific societies such as the IFCC are called to foster equitable implementation of AI by promoting access to training, infrastructure, and governance frameworks thus ensuring that AI contributes meaningfully to global health solidarity and equity.
Indexed as
Identifiers
41459176PMC12743338What 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.