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Diagnostics
Special Issues
Advances in Diagnosis and Management of Neuropsychiatric Disorders
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Advances in Diagnosis and Management of Neuropsychiatric Disorders

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 1238

Special Issue Editor

Dr. Jesús Ramírez-Bermúdez

E-Mail Website
Guest Editor
National Institute of Neurology and Neurosurgery, Ciudad de México, Mexico
Interests: neuropsychiatry; mania; MRI

Special Issue Information

Dear Colleagues,

With the ongoing changes in social pressure and our contemporary lifestyles, the incidence of neuropsychiatric disorders (including autism, depression, mania, etc.) is on the rise, becoming a global health issue. Due to these disorders’ complex and diverse symptoms and the fact that many diseases overlap, there are many difficulties in diagnosis and a high risk of misdiagnosis and missed diagnosis. This Special Issue aims to share the latest advancements in the diagnosis and management of neuropsychiatric disorders, explore pathogenic mechanisms, focus on the latest diagnostic technologies, and help patients receive timely and correct treatment. The scope includes but is not limited to the following:

  1. Pathogenesis of neuropsychiatric disorders;
  2. Imaging diagnosis of neuropsychiatric disorders;
  3. Biomarkers in the diagnosis and management of neuropsychiatric disorders;
  4. Prognostic evaluation of neuropsychiatric disorder treatment.

We welcome your contributions.

Dr. Jesús Ramírez-Bermúdez
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neuropsychiatric disorders
  • autism
  • mania
  • depression
  • imaging
  • pathogenesis

Published Papers (1 paper)

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Research

14 pages, 2175 KiB  
Article
AI-Enhanced Predictive Modeling for Identifying Depression and Delirium in Cardiovascular Patients Scheduled for Cardiac Surgery
by Karina Nowakowska, Antonis Sakellarios, Jakub Kaźmierski, Dimitrios I. Fotiadis and Vasileios C. Pezoulas
Diagnostics 2024, 14(1), 67; https://doi.org/10.3390/diagnostics14010067 - 27 Dec 2023
Cited by 1 | Viewed by 1081
Abstract
Several studies have demonstrated a critical association between cardiovascular disease (CVD) and mental health, revealing that approximately one-third of individuals with CVD also experience depression. This comorbidity significantly increases the risk of cardiac complications and mortality, a risk that persists regardless of traditional [...] Read more.
Several studies have demonstrated a critical association between cardiovascular disease (CVD) and mental health, revealing that approximately one-third of individuals with CVD also experience depression. This comorbidity significantly increases the risk of cardiac complications and mortality, a risk that persists regardless of traditional factors. Addressing this issue, our study pioneers a straightforward, explainable, and data-driven pipeline for predicting depression in CVD patients. Methods: Our study was conducted at a cardiac surgical intensive care unit. A total of 224 participants who were scheduled for elective coronary artery bypass graft surgery (CABG) were enrolled in the study. Prior to surgery, each patient underwent psychiatric evaluation to identify major depressive disorder (MDD) based on the DSM-5 criteria. An advanced data curation workflow was applied to eliminate outliers and inconsistencies and improve data quality. An explainable AI-empowered pipeline was developed, where sophisticated machine learning techniques, including the AdaBoost, random forest, and XGBoost algorithms, were trained and tested on the curated data based on a stratified cross-validation approach. Results: Our findings identified a significant correlation between the biomarker “sRAGE” and depression (r = 0.32, p = 0.038). Among the applied models, the random forest classifier demonstrated superior accuracy in predicting depression, with notable scores in accuracy (0.62), sensitivity (0.71), specificity (0.53), and area under the curve (0.67). Conclusions: This study provides compelling evidence that depression in CVD patients, particularly those with elevated “sRAGE” levels, can be predicted with a 62% accuracy rate. Our AI-driven approach offers a promising way for early identification and intervention, potentially revolutionizing care strategies in this vulnerable population. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Management of Neuropsychiatric Disorders)
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