The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review

This narrative literature review undertakes a comprehensive examination of the burgeoning field, tracing the development of artificial intelligence (AI)-powered tools for depression and anxiety detection from the level of intricate algorithms to practical applications. Delivering essential mental health care services is now a significant public health priority. In recent years, AI has become a game-changer in the early identification and intervention of these pervasive mental health disorders. AI tools can potentially empower behavioral healthcare services by helping psychiatrists collect objective data on patients' progress and tasks. This study emphasizes the current understanding of AI, the different types of AI, its current use in multiple mental health disorders, advantages, disadvantages, and future potentials. As technology develops and the digitalization of the modern era increases, there will be a rise in the application of artificial intelligence in psychiatry; therefore, a comprehensive understanding will be needed. We searched PubMed, Google Scholar, and Science Direct using keywords for this. In a recent review of studies using electronic health records (EHR) with AI and machine learning techniques for diagnosing all clinical conditions, roughly 99 publications have been found. Out of these, 35 studies were identified for mental health disorders in all age groups, and among them, six studies utilized EHR data sources. By critically analyzing prominent scholarly works, we aim to illuminate the current state of this technology, exploring its successes, limitations, and future directions. In doing so, we hope to contribute to a nuanced understanding of AI's potential to revolutionize mental health diagnostics and pave the way for further research and development in this critically important domain.

Ampreloxetine Versus Droxidopa in Neurogenic Orthostatic Hypotension: A Comparative Review

Neurogenic orthostatic hypotension (nOH) is a disabling problem of autonomic dysfunction in patients with Parkinson's disease, which is associated with poor quality of life and higher mortality rates. The purpose of this literature review was to explore and compare the efficacy and safety of droxidopa (an existing treatment) and ampreloxetine (a newer medication) in the treatment of nOH. We used a mixed-method literature review that addresses the epidemiology, pathophysiology, and pharmacological and non-pharmacological management of nOH in Parkinson's disease in a general way, with a more exploratory approach to droxidopa- and ampreloxetine-controlled trial studies. We included a total of 10 studies of randomized controlled trials with eight studies focused on droxidopa and two studies focused on ampreloxetine. These two drugs were analyzed and compared based on the collected individual study results. Treatment of nOH in Parkinson's disease patients with droxidopa or ampreloxetine showed clinically meaningful and statistically significant improvements relative to placebo on the components of the OHSA (Orthostatic Hypotension Symptom Assessment) composite score and OHDAS (Orthostatic Hypotension Daily Activity Scale composite scores) composite score. Droxidopa had an improved effect on daily activities, with an associated increase in standing systolic blood pressure (BP), but the long-term efficacy of droxidopa has not been documented. Standing systolic BP was maintained by ampreloxetine and worsened after the withdrawal phase. This highlights the importance of conducting further research which will help us to improve the therapeutic approach for patients with nOH and Parkinson's disease.