0% Complete
صفحه اصلی
/
International Conference on Artificial Intelligence; City, Industry and Health
A Review of Machine Learning Methods for Autism Diagnosis
نویسندگان :
Ali Emami
1
Nasim Noorafza
2
1- Department of Computer Engineering, Na.C, Islamic Azad University, Najafabad, Iran
2- Department of Computer Engineering, Na.C, Islamic Azad University, Najafabad, Iran
کلمات کلیدی :
Autism Spectrum Disorder،Ensemble Methods،Machine Learning،Machine Learning in Medicine
چکیده :
Autism Spectrum Disorder (ASD) is a neurological condition characterized by difficulties in social interactions, communication, and repetitive behaviors. Although its primary cause is genetic, early detection is critically important, and the application of machine learning offers a promising solution for faster and more cost-effective diagnosis. However, studies in the field of ASD diagnosis using machine learning face several challenges. One major limitation is the reliance on single models, which often struggle to simultaneously capture the complex features of autism due to limited generalizability. In addition, many classification models depend on labeled data, and their performance significantly degrades when the data is noisy or of small volume. Moreover, most machine learning methods—especially those based on single algorithms—are unable to integrate information from different aspects of the data. In contrast, combining multiple perspectives can enhance the accuracy and robustness of detection. Given these limitations, the use of ensemble methods, which combine multiple machine learning models to leverage the strengths of each, presents an effective solution. In this paper, we review classical and standalone machine learning methods, and finally, we present our proposed approach.
لیست مقالات
لیست مقالات بایگانی شده
Comparative Analysis of U-Net and U-Net (Xception) for CT-Based Segmentation of Target Volume and Organs At-Risk in Left Breast Cancer
Hajar Ahmadi - Azimeh NV Dehkordi - Farhad Azimifar - Seied Rabi Mahdavi - Mahnaz Roayaei
نقش شهرسازی در بهینهسازی شبکههای توزیع انرژی در مناطق شهری: مطالعه موردی منطقه 22 شهر تهران
فرشته احمدی - فرشته یمینی نجف آبادی
بهرهبرداری اقتصادی و سازگار با محیطزیست یک نیروگاه مجازی با نفوذ گستردهی منابع انرژی تجدیدپذیر
احسان شکوهمند - مصطفی درویشی - مهرداد طهماسبی
Impact of Using ChatGPT as an AI Tool on Speaking Complexity, Accuracy, and Fluency Among Iranian EFL Learners
Samira Beheshti - Omid Tabatabaei - Hadi Salehi
تحلیل مقایسهای اینورترهای خورشیدی: بررسی تأثیر شرایط محیطی، هزینه بر عملکرد و راندمان سامانههای فتوولتائیک
علی فرج زاده - مجید محمدیان - امین علیان - محمد جبیری
Forecasting Electricity Price Spikes in Competitive Markets Using a Hybrid Deep Learning Framework with SHAP and Grey Wolf Optimization
Hossein Shahinzadeh - Hamed Nafisi - Mahtab Bagheri - Saiedeh Mehrabani-Najafabadi - Sudeep Tanwar - Francisco Jurado
The Evolution of Smart Grids: Decentralization, Communication, and Economic Impact
Saiedeh Mehrabani-Najafabadi - Hossein Shahinzadeh - Hamed Nafisi - Shohreh Azani - Ehsan Etemadnia - Ali Karimi
PIMA: Power Imbalance Management Agent as a Distributed Supply Chain Management System
Paniz MohsenNia - Saeed Kafshdouzzadeh - Ehsan Shahi - Amirreza Khanzadeh Khaneqah - Alireza Fereidunian
نقش اقتصادی یراق کمربندی در بهسازی سکوی تابلوها و ترانسفورماتورهای هوایی و شبکه های هوایی
ابراهیم گوگونانی - حمیدرضا شهبازی - محسن سلیمی - متین گوگونانی - احمد آقاجانی
Automated Metaphor Identification: Applying Artificial Intelligence to MIP for detecting Emotion-Related Conceptual Metaphors in Philip Caputo’s A Rumor of War
Parivash Esmaeili
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 41.6.0