The Role of Artificial Intelligence in Managing Bipolar Disorder: A New Frontier in Patient Care

<b>Background/Objectives:</b> Bipolar disorder (BD) is a complex and chronic mental health condition that poses significant challenges for both patients and healthcare providers. Traditional treatment methods, including medication and therapy, remain vital, but there is increasing interest in the application of artificial intelligence (AI) to enhance BD management. AI has the potential to improve mood episode prediction, personalize treatment plans, and provide real-time support, offering new opportunities for managing BD more effectively. Our primary objective was to explore the potential role of AI in transforming the management of BD, specifically in mood tracking, prediction, and personalized treatment regimens. <b>Methods</b>: To explore the potential role of AI in transforming BD management, we conducted a review of recent literature using key search terms. We included studies that discussed AI applications in mood tracking, prediction, and treatment personalization. The studies were selected based on their relevance to AI's role in BD management, with attention to the PICO criteria: Population-individuals diagnosed with BD; Intervention-AI tools for mood prediction, treatment personalization, and real-time support; Comparison-traditional treatment methods (when available); Outcome-measures of mood episode prediction, treatment effectiveness, and improvements in patient care. <b>Results</b>: The findings from recent research reveal promising developments in the use of AI for BD management. Studies suggest that AI-powered tools can enable more proactive and personalized care, improving treatment outcomes and reducing the burden on healthcare professionals. AI's ability to analyze data from wearable devices, smartphones, and even social media platforms provides valuable insights for early detection and more dynamic treatment adjustments. <b>Conclusions</b>: While AI's application in BD management is still in its early stages, it presents transformative potential for improving patient care. However, further research and development are crucial to fully realize AI's potential in supporting BD patients and optimizing treatment efficacy.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2025-04-07
DOI
https://doi.org/10.3390/jcm14072515
Citations
11
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
7.20
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Role of Artificial Intelligence in Managing Bipolar Disorder: A New Frontier in Patient Care

Edita Grego, Sanja Djurdjevic, Dragana P. Jovic, Jelena Milić et al.
11 citations
Journal of Clinical Medicine
Artificial Intelligence in Healthcare and Education
7.20
article

The Role of Artificial Intelligence in Managing Bipolar Disorder: A New Frontier in Patient Care

Edita Grego, Sanja Djurdjevic, Dragana P. Jovic, Jelena Milić, Rosa Šapić, Veroslava Stanković, Iva Zrnic
article en
11 citations

Abstract

<b>Background/Objectives:</b> Bipolar disorder (BD) is a complex and chronic mental health condition that poses significant challenges for both patients and healthcare providers. Traditional treatment methods, including medication and therapy, remain vital, but there is increasing interest in the application of artificial intelligence (AI) to enhance BD management. AI has the potential to improve mood episode prediction, personalize treatment plans, and provide real-time support, offering new opportunities for managing BD more effectively. Our primary objective was to explore the potential role of AI in transforming the management of BD, specifically in mood tracking, prediction, and personalized treatment regimens. <b>Methods</b>: To explore the potential role of AI in transforming BD management, we conducted a review of recent literature using key search terms. We included studies that discussed AI applications in mood tracking, prediction, and treatment personalization. The studies were selected based on their relevance to AI's role in BD management, with attention to the PICO criteria: Population-individuals diagnosed with BD; Intervention-AI tools for mood prediction, treatment personalization, and real-time support; Comparison-traditional treatment methods (when available); Outcome-measures of mood episode prediction, treatment effectiveness, and improvements in patient care. <b>Results</b>: The findings from recent research reveal promising developments in the use of AI for BD management. Studies suggest that AI-powered tools can enable more proactive and personalized care, improving treatment outcomes and reducing the burden on healthcare professionals. AI's ability to analyze data from wearable devices, smartphones, and even social media platforms provides valuable insights for early detection and more dynamic treatment adjustments. <b>Conclusions</b>: While AI's application in BD management is still in its early stages, it presents transformative potential for improving patient care. However, further research and development are crucial to fully realize AI's potential in supporting BD patients and optimizing treatment efficacy.

Journal of Clinical MedicineVol. 14(7)
University of Bijeljina (BA), Institute of Public Health of Serbia (RS)
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
7.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.