Evidence map›Paper›PMID 40988064›Full record

ReviewEuropean journal of medical research2025

Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives.

Yosri A Fahim, Ibrahim W Hasani, Samer Kabba, Waleed Mahmoud Ragab

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

76 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yosri A FahimDepartment of Basic Medical Sciences, Health Sector, Galala University, Suez, 43511, Egypt. Yosri.fahim@gu.edu.eg.ORCID http://orcid.org/0000-0002-1009-7577
Ibrahim W HasaniFaculty of Pharmacy, Al-Andalus University for Medical Sciences, Qadmus, Tartus, Syrian Arab Republic.
Samer KabbaFaculty of Pharmacy, Al-Andalus University for Medical Sciences, Qadmus, Tartus, Syrian Arab Republic.
Waleed Mahmoud RagabDepartment of Anatomy and Embryology, Faculty of Medicine, Galala University, Suez, 43511, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare systems worldwide face growing challenges, including rising costs, workforce shortages, and disparities in access and quality, particularly in low- and middle-income countries. Artificial intelligence (AI) has emerged as a transformative tool capable of addressing these issues by enhancing diagnostics, treatment planning, patient monitoring, and healthcare efficiency. AI's role in modern medicine spans disease detection, personalized care, drug discovery, predictive analytics, telemedicine, and wearable health technologies. Leveraging machine learning and deep learning, AI can analyze complex data sets, including electronic health records, medical imaging, and genomic profiles, to identify patterns, predict disease progression, and recommend optimized treatment strategies. AI also has the potential to promote equity by enabling cost-effective, resource-efficient solutions in low-resource and remote settings, such as mobile diagnostics, wearable biosensors, and lightweight algorithms. Successful deployment requires addressing critical challenges, including data privacy, algorithmic bias, model interpretability, regulatory oversight, and maintaining human clinical oversight. Emphasizing scalable, ethical, and evidence-driven implementation, key strategies include clinician training in AI literacy, adoption of resource efficient tools, global collaboration, and robust regulatory frameworks to ensure transparency, safety, and accountability. By complementing rather than replacing healthcare professionals, AI can reduce errors, optimize resources, improve patient outcomes, and expand access to quality care. This review emphasizes the responsible integration of AI as a powerful catalyst for innovation, sustainability, and equity in healthcare delivery worldwide.

Indexed as

Artificial IntelligenceDelivery of Health CareHumansPrecision MedicineTelemedicineArtificial intelligenceDiagnosticsEthical challengesHealthcare systemsPersonalized medicine

Identifiers

PMID40988064
PMCPMC12455834

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.