Evidence map›Paper›PMID 39763580›Full record

ArticleHealth science reports2025

The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency.

Md Faiyazuddin, Syed Jalal Q Rahman, Gaurav Anand, Reyaz Kausar Siddiqui, Rachana Mehta, Mahalaqua Nazli Khatib, Shilpa Gaidhane, Quazi Syed Zahiruddin, Arif Hussain, Ranjit Sah

Abstract read
In one paragraph

Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 8 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

70 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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  7. Guideline
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10 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

10 authors.

Md FaiyazuddinSchool of Pharmacy Al-Karim University Katihar India.
Syed Jalal Q RahmanNovo Nordisk Inc. Plainsboro New Jersey USA.ORCID 0009-0001-9021-9502
Gaurav AnandMedical Writing Tata Consultancy Services Noida Uttar Pradesh India.ORCID 0000-0001-9227-7143
Reyaz Kausar SiddiquiEgo Pharmaceuticals Knutsford UK.
Rachana MehtaDr Lal PathLabs Nepal, Chandol Kathmandu 44600 Nepal.ORCID 0000-0003-4771-4089
Mahalaqua Nazli KhatibDivision of Evidence Synthesis, Global Consortium of Public Health and Research Datta Meghe Institute of Higher Education Wardha India.
Shilpa GaidhaneOne Health Centre (COHERD), Jawaharlal Nehru Medical College Datta Meghe Institute of Higher Education Wardha India.
Quazi Syed ZahiruddinGlobal Health Academy, Division of Evidence Synthesis, School of Epidemiology and Public Health and Research, Jawaharlal Nehru Medical College Datta Meghe Institute of Higher Education and Research Wardha India.
Arif HussainSchool of Life Sciences Manipal Academy of Higher Education-Dubai Campus Dubai United Arab Emirates.
Ranjit SahDepartment of Microbiology Dr D. Y. Patil Medical College, Hospital and Research Centre, Dr D. Y. Patil Vidyapeeth (Deemed-to-be-University) Pune Maharashtra India.ORCID 0000-0002-2695-8714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment. Methods: This review analyzes the impact of AI on healthcare using data from the Web of Science (2014-2024), focusing on keywords like AI, ML, and healthcare applications. It examines the uses and effects of AI on healthcare by synthesizing recent literature and real-world case studies, such as Google Health and IBM Watson Health, highlighting AI technologies, their useful applications, and the difficulties in putting them into practice, including problems with data security and resource limitations. The review also discusses new developments in AI, and how they can affect society. Results: The findings demonstrate how AI is enhancing the skills of medical professionals, enhancing diagnosis, and opening the door to more individualized treatment plans, as reflected in the steady rise of AI-related healthcare publications from 158 articles (3.54%) in 2014 to 731 articles (16.33%) by 2024. Core applications like remote monitoring and predictive analytics improve operational effectiveness and patient involvement. However, there are major obstacles to the mainstream implementation of AI in healthcare, including issues with data security and budget constraints. Conclusion: Healthcare may be transformed by AI, but its successful use requires ethical and responsible use. To meet the changing demands of the healthcare sector and guarantee the responsible application of AI technologies, the evaluation highlights the necessity of ongoing research, instruction, and multidisciplinary cooperation. In the future, integrating AI responsibly will be essential to optimizing its advantages and reducing related dangers.

Indexed as

AI ethicsAI technologiesdata Analyticsdigital HealthHealthcare Business

Identifiers

PMID39763580
PMCPMC11702416

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.