ReviewJournal of pharmacy & bioallied sciences2025
Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review.
Review in Journal of pharmacy & bioallied sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Bridging Andrology and Oncology: Prognostic Indicators of Cancer Among Infertile Men.Current issues in molecular biology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) is revolutionizing psychopharmacology and psychological research, enhancing diagnostics, treatments, and accessibility. This review examines AI's transformative role, applications, challenges, and future directions in these fields. AI tools improve diagnostic accuracy by analyzing brain imaging, health records, and behavioral data, enabling precise identification of disorders like depression and schizophrenia. Personalized medicine, powered by AI, predicts individual medication responses, minimizing side effects and optimizing outcomes. Innovative therapies, such as virtual psychotherapists and AI-assisted social robots, expand access to mental health care in underserved areas. AI in psycho-radiology leverages brain imaging for tailored interventions and treatment prediction, while wearable technologies and digital phenotyping enable real-time mental health monitoring and early intervention. However, challenges persist, including data privacy, algorithmic bias, ethical dilemmas, and regulatory hurdles, emphasizing the need for robust governance. Future advancements include refining diagnostics through machine learning and natural language processing and integrating collaborative AI models for holistic, personalized care. Ensuring ethical, transparent, and culturally sensitive applications is essential for trust and sustainability. This review aims to explore the transformative potential of AI in psychopharmacology and psychological research, highlighting its ability to revolutionize mental health care while addressing the challenges inherent to its adoption and implementation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.