Deep Learning for Emotional Distress: An Enhanced Hybrid Optimization Model with Ensemble Learning

The main leading cause of suicidal deaths in the 21st century is the mental illness called depression. With that said there are different traditional methods to cure depression for an individual, medication, and psychiatric therapy, and the development of modern drugs in the category of anti-depression drugs has made significant growth. But still, the detection of depression has still been a challenge, and this gap will be completed with modern technology, this paper reviews those methods and gives a clear understanding of different methods in the perspective of This review seeks to provide a complete overview of the various approaches and techniques used for recognizing and evaluating depressive disorders by a careful analysis of the available research and empirical studies. By examining the methods in the angle of gaps advantages and disadvantages, the effectiveness of implementation, and accuracy thus provides a great for researchers and clinicians.

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Published
2025-03-28
DOI
https://doi.org/10.1109/ngise64126.2025.11085180
Primary Topic
Machine Learning in Healthcare
Type
article
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article

Deep Learning for Emotional Distress: An Enhanced Hybrid Optimization Model with Ensemble Learning

Nikhil E. Karale, Vijay S. Gulhane
Machine Learning in Healthcare
article

Deep Learning for Emotional Distress: An Enhanced Hybrid Optimization Model with Ensemble Learning

Nikhil E. Karale, Vijay S. Gulhane
article en

Abstract

The main leading cause of suicidal deaths in the 21st century is the mental illness called depression. With that said there are different traditional methods to cure depression for an individual, medication, and psychiatric therapy, and the development of modern drugs in the category of anti-depression drugs has made significant growth. But still, the detection of depression has still been a challenge, and this gap will be completed with modern technology, this paper reviews those methods and gives a clear understanding of different methods in the perspective of This review seeks to provide a complete overview of the various approaches and techniques used for recognizing and evaluating depressive disorders by a careful analysis of the available research and empirical studies. By examining the methods in the angle of gaps advantages and disadvantages, the effectiveness of implementation, and accuracy thus provides a great for researchers and clinicians.

Sant Gadge Baba Amravati University (IN)
Reduced inequalities
Openalex Percentile: Top 89%
Machine Learning in Healthcare
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