The Pros and Cons of Using Machine Learning and Interpretable Machine Learning Methods In Psychiatry Detection Applications, Specifically Depression Disorder: A Brief Review.
원문 초록
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.
함께 살펴볼 논문
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AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
Remember Past, Anticipate Future: Learning Continual Multimodal Misinformation Detectors
Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
Leveraging Predictive Equivalence in Decision Trees
Characterizing Linguistic Shifts in Croatian News via Diachronic Word Embeddings
How Grounded is Wikipedia? A Study on Structured Evidential Support
토론
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