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Federico, C., Campagner, A., et al. (2021) The Importance of Being External. Methodological Insights for the External Validation of Machine Learning Models in Medicine. Computer Methods and Programs in Biomedicine, 208, Article 106288.
https://doi.org/10.1016/j.cmpb.2021.106288

has been cited by the following article:

• TITLE: Evaluating Pharmacological and Rehabilitation Strategies for Effective Management of Bipolar Disorder: A Comprehensive Clinical Study

  AUTHORS: Rocco de Filippis, Abdullah Al Foysal

  KEYWORDS: Bipolar Disorder (BD), Pharmacotherapy (PT), Rehabilitation Interventions (RI), Hamilton Depression Scale (HAM-D), Yale-Brown Obsessive Compulsive Scale (Y-BOCS), Mania Scale (MS), Machine learning (ML) and Artificial Intelligence (AI).

  JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.15 No.7, July 26, 2024

  ABSTRACT: Bipolar disorder presents significant challenges in clinical management, characterized by recurrent episodes of depression and mania often accompanied by impairment in functioning. This study investigates the efficacy of pharmacological interventions and rehabilitation strategies to improve patient outcomes and quality of life. Utilizing a randomized controlled trial with multiple treatment arms, participants will receive pharmacotherapy, polypharmacotherapy, rehabilitation interventions, or combination treatments. Outcome measures will be assessed using standardized scales, including the Hamilton Depression Scale, Yale-Brown Obsessive Compulsive Scale (Y-BOCS), and Mania Scale. Preliminary data suggest improvements in symptom severity and functional outcomes with combination treatments. This research aims to inform clinical practice, guide treatment decisions, and ultimately enhance the quality of care for individuals living with bipolar disorder. Findings will be disseminated through peer-reviewed journals and scientific conferences to advance knowledge in this field.