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The Pros and Cons of Using Machine Learning and Interpretable Machine Learning Methods in psychiatry detection applications, specifically depression disorder: A Brief Review

arXiv 2311.06633 ↗First posted 11 Nov 2023cs.LG cs.AIcited by 0

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Abstract (arXiv)

The COVID-19 pandemic has forced many people to limit their social activities, which has resulted in a rise in mental illnesses, particularly depression. To diagnose these illnesses with accuracy and speed, and prevent severe outcomes such as suicide, the use of machine learning has become increasingly important. Additionally, to provide precise and understandable diagnoses for better treatment, AI scientists and researchers must develop interpretable AI-based solutions. This article provides an overview of relevant articles in the field of machine learning and interpretable AI, which helps to understand the advantages and disadvantages of using AI in psychiatry disorder detection applications.

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References · 11

  1. 2018RuleMatrix: Visualizing and Understanding Classifiers with Rulescited by 62
  2. 2023Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamicscited by 6
  3. 2022Modern Views of Machine Learning for Precision Psychiatrycited by 5
  4. 2022Interpretable AI for policy-making in pandemicscited by 5
  5. 2023A Generalised Deep Meta-Learning Model for Automated Quality Control of Cardiovascular Magnetic Resonance Imagescited by 4
  6. 2023Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studiescited by 4
  7. 2021Predicting Mood Disorder Symptoms with Remotely Collected Videos Using an Interpretable Multimodal Dynamic Attention Fusion Networkcited by 2
  8. 2021Automatic Multi-Class Cardiovascular Magnetic Resonance Image Quality Assessment using Unsupervised Domain Adaptation in Spatial and Frequency Domainscited by 2
  9. 2022RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosiscited by 2
  10. 2022Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoTcited by 2
  11. 2023A Picture May Be Worth a Thousand Lives: An Interpretable Artificial Intelligence Strategy for Predictions of Suicide Risk from Social Media Imagescited by 1

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