PSIXIK BUZILISHLARNI TUSHUNISHDA NEYROBIOLOGIK VA SUN’IY INTELLEKTGA ASOSLANGAN YONDASHUVLARNING DOLZARB MUAMMOLARI

Authors

  • Shodiyeva Feruza Beshimovna Author

Keywords:

Kalit so’zlar psixik buzilishlar, neyrobiologiya, sun’iy intellekt, biomarkerlar, EEG, aniq psixiatriya, raqamli tibbiyot.

Abstract

Annotatsiya  Mazkur  maqolada  psixik  buzilishlarni  tushuntirish  va 
tashxislashda  neyrobiologik  yondashuvlar  hamda  sun’iy  intellekt  (SI) 
texnologiyalarining  o‘rni,  imkoniyatlari  va  dolzarb  muammolari  tahlil  qilinadi. 
Zamonaviy  psixiatriyada  miya  faoliyatining  neyron  mexanizmlarini  aniqlash, 
biomarkerlarni  izlash  va  katta  hajmdagi  klinik  ma’lumotlarni  tahlil  qilishda  SI 
vositalaridan foydalanish tobora kengayib bormoqda. Biroq ushbu yondashuvlar qator 
metodologik,  texnologik  va  etik  muammolar  bilan  hamroh  bo‘lmoqda.  Maqolada 
ushbu  muammolar  tizimli  ravishda  yoritilib,  ularni  bartaraf  etish  yo‘nalishlari 
muhokama qilinadi. 

References

1. Baydili I., Tasci B., Tasci G. Artificial intelligence in psychiatry: A review of

biological and behavioral data analyses // Diagnostics. – 2025. – Vol. 15, No. 4. –

P. 434. – DOI: 10.3390/diagnostics15040434.

2. Sun J. Practical artificial intelligence application in psychiatry: historical review

and clinical insights // Molecular Psychiatry. – 2025. – Vol. 30. – P. 1–12. – DOI:

10.1038/s41380-025-03072-3.

3. Zheng H., Zhang X. Psychiatry in the age of artificial intelligence: transforming

theory, practice, and medical education // Frontiers in Public Health. – 2025. – Vol.

13. – Article ID 12515848. – DOI: 10.3389/fpubh.2025.12515848.

4. Rony M.K.K., Rahman M.M., Islam M.R. Artificial intelligence in psychiatry: A

systematic review and meta-analysis of diagnostic and therapeutic efficacy //

Journal of Psychiatric Research. – 2025. – Vol. 171. – P. 45–58. – DOI:

10.1016/j.jpsychires.2025.01.012.

5. Wright S.N. Generative artificial intelligence for precision neuroimaging biomarker

development in psychiatry // NeuroImage. – 2024. – Vol. 276. – Article ID 120210.

– DOI: 10.1016/j.neuroimage.2023.120210.

6. Prégent J., Côté A., Bouchard S. Applications of artificial intelligence in psychiatry

and medical education // JMIR Medical Education. – 2025. – Vol. 11, No. 1. –

e75238. – DOI: 10.2196/75238.

7. Ngwoke I., Agboola A.O. Artificial intelligence in psychiatry: transforming

diagnosis, personalized care and future directions // Exploration of Digital Health

Technologies. – 2025. – Vol. 3. – P. 210–223. – DOI: 10.37349/edht.2025.00045.

8. Nassibi A., Keshavarzian A., Hosseini M. EEG-based machine intelligence

algorithms for depression diagnosis and monitoring: A systematic review //

Biomedical Signal Processing and Control. – 2025. – Vol. 88. – Article ID 105536.

– DOI: 10.1016/j.bspc.2024.105536.

9. Benrimoh D., Parr T., Adams R.A. Computational psychiatry and affective states:

bridging neuroscience and artificial intelligence // Trends in Cognitive Sciences. –

2025. – Vol. 29, No. 3. – P. 198–211. – DOI: 10.1016/j.tics.2024.12.004.

10. Demir E., Coşkun Y. Artificial intelligence in psychiatry: current trends, clinical

applications and research gaps // Asian Journal of Psychiatry. – 2026. – Vol. 87. –

Article ID 103684. – DOI: 10.1016/j.ajp.2025.103684.

Published

2026-01-27

How to Cite

Shodiyeva Feruza Beshimovna. (2026). PSIXIK BUZILISHLARNI TUSHUNISHDA NEYROBIOLOGIK VA SUN’IY INTELLEKTGA ASOSLANGAN YONDASHUVLARNING DOLZARB MUAMMOLARI . Ta’lim Innovatsiyasi Va Integratsiyasi, 62(1), 74-77. https://journalss.org/index.php/tal/article/view/16714