Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression

Caglar Uyulan; Emel Sari Gokten

doi:10.5455/PBS.20220602052257

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Original Research

PBS. 2022; 12(4): 176-187

doi: 10.5455/PBS.20220602052257

Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression

Caglar Uyulan, Emel Sari Gokten.

Abstract
Background: Although attention-deficit/hyperactivity disorder (ADHD) symptoms decrease with the factors such as age, many individuals keep suffering from the disorder in adolescence and adulthood.
Objective: In this paper, a deep learning algorithm was built to forecast the prognosis of ADHD, using the patient's clinical features, the measurement of their response to treatment, and the degree of improvement seen after six years of follow-up.
Participants and Settings: The clinical findings such as socio-demographic data of 433 patients followed by the child and adolescent psychiatry department for an average of 6 years with diagnoses of ADHD, and ADHD sub-type, accompanying oppositional/conduct disorders, other psychiatric and organic disorders, the effectiveness of psychotherapy and medication on attention, academic status, and behavioral problems were used to help predict prognosis.
Methods: A deep neural network (DNN) learning-based regressor was used to make a prediction model.
Results: The results obtained from the DNN regression model achieved accurate predictions for all outputs. The mean error for all outputs was evaluated as mean-squared error (mse) and 0.0068 mean-absolute error (mae), respectively. The R-value was evaluated as 0.91316. It was proven that the model prediction power was adequate as tested with these metrics.
Conclusions: This methodology improves the prediction of ADHD prognosis and provides a robust predictive model. Studies with larger samples may support the results.

Key words: ADHD; prognosis; artificial intelligence; deep neural network learning-based regressor; deep learning

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Pubmed Style

Uyulan C, Gokten ES. Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. PBS. 2022; 12(4): 176-187. doi:10.5455/PBS.20220602052257

Web Style

Uyulan C, Gokten ES. Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. https://www.pbsciences.org/?mno=50273 [Access: April 07, 2024]. doi:10.5455/PBS.20220602052257

AMA (American Medical Association) Style

Uyulan C, Gokten ES. Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. PBS. 2022; 12(4): 176-187. doi:10.5455/PBS.20220602052257

Vancouver/ICMJE Style

Uyulan C, Gokten ES. Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. PBS. (2022), [cited April 07, 2024]; 12(4): 176-187. doi:10.5455/PBS.20220602052257

Harvard Style

Uyulan, C. & Gokten, . E. S. (2022) Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. PBS, 12 (4), 176-187. doi:10.5455/PBS.20220602052257

Turabian Style

Uyulan, Caglar, and Emel Sari Gokten. 2022. Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. Psychiatry and Behavioral Sciences, 12 (4), 176-187. doi:10.5455/PBS.20220602052257

Chicago Style

Uyulan, Caglar, and Emel Sari Gokten. "Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression." Psychiatry and Behavioral Sciences 12 (2022), 176-187. doi:10.5455/PBS.20220602052257

MLA (The Modern Language Association) Style

APA (American Psychological Association) Style

Uyulan, C. & Gokten, . E. S. (2022) Prediction of Long-term Prognosis of Children with Attention-deficit/Hyperactivity Disorder in Conjunction with Deep Neural Network Regression. Psychiatry and Behavioral Sciences, 12 (4), 176-187. doi:10.5455/PBS.20220602052257

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