International Conference on Computer and Knowledge Engineering

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Improving ADHD Detection with Cost-Sensitive LightGBM

Authors :

Behnam Yousefimehr¹ Mehdi Ghatee² Ali Heydari³

1- Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran 2- Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran 3- Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran

Keywords :

ADHD،Mental Health،Machine Learning،Cost-Sensitive،LightGBM

Abstract :

Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder requiring timely and accurate diagnosis for effective treatment. In this study, we present a novel approach using a cost-sensitive LightGBM (Light Gradient Boosting Machine) model to enhance the prediction of ADHD. Our key contribution lies in the integration of cost-sensitive learning, which prioritizes minimizing the misclassification costs associated with false negatives and false positives, critical in medical diagnostics. Additionally, we leverage the computational efficiency and speed of LightGBM, a gradient boosting framework known for its high performance in handling complex data structures. Our results demonstrate that the cost-sensitive LightGBM model not only improves predictive accuracy but also significantly reduces the time required for training and inference, making it a viable tool for real-world ADHD screening applications. This study highlights the importance of incorporating cost-sensitive algorithms in medical predictions to achieve a balanced trade-off between accuracy and resource efficiency.

Papers List

List of archived papers

Balanced Learning with Optimized Extra Trees Classifier for Reliable Lithology Identification in Imbalanced Well Log Data

Ali Daneshpour - Behnam Yousefimehr - Mehdi Ghatee

Damage Detection After the Earthquake Using Sentinel-1 and 2 Images and Machine Learning Algorithms (Case Study: Sarpol-e Zahab Earthquake)

Niloofar Alizadeh - Behnam Asghari Beirami - Mehdi Mokhtarzade

Age Estimation Based on Facial Images Using Hybrid Features and Particle Swarm Optimization

NILOUFAR MEHRABI - SAYED PEDRAM HAERI BOROUJENI

Enhanced Melanoma Detection: An Improved Deformable DETR Model with Efficient Channel Attention

Amirreza Rouhbakhshmeghrazi - Shayan Nalbandian - Sheida Shadman - Mohammad Reza Hassannezhad - Shuyuan Yang - Bo Li

Data-Optimized Dry Rock Property Prediction Using Ensemble and Kernel-Based ML Methods

Esmael Makarian - Hassanreza Ghasemitabar - Alireza Behinrad - Mahdi Fathi - Andisheh Alimoradi - Ayub Elyasi

An intelligent linguistic error detection approach to automated diagnosis of Dyslexia disorder in Persian speaking children

Fatemeh Asghari - Mahsa Khorasani - Mohsen Kahani - Seyed Amir Amin Yazdi - Mahdi Arkhodi Ghalenoei

Capsule Routing over Stacked GCN-GAT Embeddings with Negative Sampling for Graph Link Prediction

Fatemeh Safari Sarvandi - Sayeh Mirzaei - Rooholah Abedian

Frame Classification in Video Capsule Endoscopy Using an Improved Capsule Network

Amirhossein Ghaemi - Habibollah Danyali - Alireza Ghaemi

Practical Implementation of Real-Time Waste Detection and Recycling based on Deep Learning for Delta Parallel Robot

Hasan Jalali - Shaya Garjani - Ahmad Kalhor - Mehdi Tale Masouleh - Parisa Yousefi

Real-time Implementation of Fuzzy Visual Servoing for a Delta Robot via Shape and Color Detection

Nooshin Najafian - Alireza Ashrafi Majd - Abbas Ansaroudi - Sahar Aghazadeh - Manizheh Zakeri - Mohammad-Reza Sayyed Noorani