Evidence map›Paper›PMID 38201418›Full record

ReviewDiagnostics (Basel, Switzerland)2024

A Systematic Review and Meta-Analysis of Artificial Intelligence Tools in Medicine and Healthcare: Applications, Considerations, Limitations, Motivation and Challenges.

Hussain A Younis, Taiseer Abdalla Elfadil Eisa, Maged Nasser, Thaeer Mueen Sahib, Ameen A Noor, Osamah Mohammed Alyasiri, Sani Salisu, Israa M Hayder, Hameed AbdulKareem Younis

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing 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

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

  1. Deep learning for early diagnosis of uveal melanoma: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  18. Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026
    Review
  19. Therapeutic Decisions in Inflammatory Bowel Disease: ChatGPT-4.0 Compared to Medical Expertise.JGH open : an open access journal of gastroenterology and hepatology · 2026
    Article
  20. Article

19 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

9 authors.

Hussain A YounisCollege of Education for Women, University of Basrah, Basrah 61004, Iraq.ORCID 0000-0002-5042-4990
Taiseer Abdalla Elfadil EisaDepartment of Information Systems-Girls Section, King Khalid University, Mahayil 62529, Saudi Arabia.
Maged NasserComputer & Information Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Thaeer Mueen SahibKufa Technical Institute, Al-Furat Al-Awsat Technical University, Kufa 54001, Iraq.
Ameen A NoorComputer Science Department, College of Education, University of Almustansirya, Baghdad 10045, Iraq.
Osamah Mohammed AlyasiriKarbala Technical Institute, Al-Furat Al-Awsat Technical University, Karbala 56001, Iraq.ORCID 0000-0002-2345-2443
Sani SalisuDepartment of Information Technology, Federal University Dutse, Dutse 720101, Nigeria.ORCID 0000-0001-9196-4507
Israa M HayderQurna Technique Institute, Southern Technical University, Basrah 61016, Iraq.
Hameed AbdulKareem YounisDepartment of Cybersecurity, College of Computer Science and Information Technology, University of Basrah, Basrah 61016, Iraq.ORCID 0000-0003-4580-9287

Funding

King Khalid University RGP2/52/44
6 · The paper itself

Abstract

Artificial intelligence (AI) has emerged as a transformative force in various sectors, including medicine and healthcare. Large language models like ChatGPT showcase AI's potential by generating human-like text through prompts. ChatGPT's adaptability holds promise for reshaping medical practices, improving patient care, and enhancing interactions among healthcare professionals, patients, and data. In pandemic management, ChatGPT rapidly disseminates vital information. It serves as a virtual assistant in surgical consultations, aids dental practices, simplifies medical education, and aids in disease diagnosis. A total of 82 papers were categorised into eight major areas, which are G1: treatment and medicine, G2: buildings and equipment, G3: parts of the human body and areas of the disease, G4: patients, G5: citizens, G6: cellular imaging, radiology, pulse and medical images, G7: doctors and nurses, and G8: tools, devices and administration. Balancing AI's role with human judgment remains a challenge. A systematic literature review using the PRISMA approach explored AI's transformative potential in healthcare, highlighting ChatGPT's versatile applications, limitations, motivation, and challenges. In conclusion, ChatGPT's diverse medical applications demonstrate its potential for innovation, serving as a valuable resource for students, academics, and researchers in healthcare. Additionally, this study serves as a guide, assisting students, academics, and researchers in the field of medicine and healthcare alike.

Indexed as

cellular imagingChatGPTdentaldiseasehealthcareimagemedicinepharmaceuticalradiology and sonar

Identifiers

PMID38201418
PMCPMC10802884

What OpenQuestion 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 OpenQuestion graph.