Page 25 - AIH-2-4

Artificial Intelligence in Health AI editorial policy ethics

Funding 5. Gogineni AK, Hitesh M, Jha PK, Sen SS, Das S, Sahu KK.
Deep learning on chest X-ray and computed tomography
None. scans for detection of COVID-19 as a part of a network-
centric digital health stack for future pandemics. Artif Intell
Conflict of interest Health. 2024;2(1):29-41.
The author has previously submitted critiques to the Journal doi: 10.36922/aih.2888
of Affective Disorders regarding AI methodologies in 6. Casiraghi JL, Lizio A, Bolognini S, et al. Exploring the viability
clinical research, which were not accepted for publication. of robotic technology integrated with Vivaldi artificial
While this perspective discusses editorial practices in AI intelligence for functional assessment in amyotrophic lateral
research – including Journal of Affective Disorders – the sclerosis. Artif Intell Health. 2024;1(4):73-84.
analysis is conducted independently, without financial doi: 10.36922/aih.3732
or institutional influence. The views expressed reflect
methodological and ethical concerns relevant to AI-driven 7. Schwingel PA, Schwingel D, De Aquino SR, et al. An
mental health research and do not stem from any personal, exploratory study on the potential of ChatGPT as an
professional, or financial stake in the journal or related AI-assisted diagnostic tool for visceral leishmaniasis. Artif
Intell Health. 2024;1(4):97-106.
entities.
doi: 10.36922/aih.3930
Author contributions 8. Luu MSK, Tuchinov BN, Prokaeva AI, Korobko DS,
This is a single-authored article. Malkova NA, Tulupov AA. Discovering predictive features
of multiple sclerosis from clinically isolated syndrome with
Ethics approval and consent to participate machine learning. Artif Intell Health. 2024;1(4):107-122.
Not applicable. doi: 10.36922/aih.4255
9. Thomas C, Prasad RR. Health-care app detection using
Consent for publication optimized clustering. Artif Intell Health. 2024;1(4):16-29.
Not applicable. doi: 10.36922/aih.2585
10. Vishwanath AB, Srinivasalu VK, Subramaniam N. Role
Availability of data of large language models in improving provider-patient
The original letters to the editors generated and analyzed in experience and interaction efficiency: A scoping review.
this expert perspective article are available upon request of Artif Intell Health. 2024;2(2):1-10.
the corresponding author. The editorial and peer responses doi: 10.36922/aih.4808
are withheld due to editorial policy. 11. Haghish EF. Differentiating adolescent suicidal and
References nonsuicidal self‐harm with artificial intelligence: Beyond
suicidal intent and capability for suicide. J Affecti Disord.
1. Umar BU, Ajao LA, Dogo EM, Ajao FJ, Atama M. Artificial 2025;378:381-391.
intelligence model for prediction of cardiovascular disease: doi: 10.1016/j.jad.2025.02.015
An empirical study. Artif Intell Health. 2023;1(1):42-56.
12. Ding Z, Zhou Y, Dai AJ, et al. Speech based suicide risk
doi: 10.36922/aih.1746 recognition for crisis intervention hotlines using explainable
2. Nawab K. Artificial intelligence scribe: A new era in medical multi‐task learning. J Affect Disord. 2025;370:392-400.
documentation. Artif Intell Health. 2024;1(4):12-15. doi: 10.1016/j.jad.2024.11.022
doi: 10.36922/aih.3103 13. Gulumbe BH. Obvious artificial intelligence‐generated
3. Kong Y, Guerrero E, Frimpong J, et al. A machine learning anomalies in published journal articles: A call for enhanced
approach to unravel client and program-specific effects in opioid editorial diligence. Learn Publ. 2024;37(4):1-5.
treatment retention. Artif Intell Health. 2024;2(1):105-113. doi: 10.1002/leap.1626
doi: 10.36922/aih.3750 14. Leveridge M. This editorial about AI in publishing
was definitely written by a human. Can Urol Assoc J.
4. Wicklem LC, San Hwang S, Lau BT, Bhave M, Chee XW.
Machine learning-driven prediction of EBNA1 inhibitors 2023;17(6):151-152.
against Epstein-Barr virus in nasopharyngeal carcinoma. doi: 10.5489/cuaj.8424
Artif Intell Health. 2024;2(1):93-104.
15. Tonmoy STI. Embeddings at BLP-2023 Task 2: Optimizing
doi: 10.36922/aih.4375 fine-tuned transformers with cost-sensitive learning for

Volume 2 Issue 4 (2025) 19 doi: 10.36922/AIH025210049