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相关论文: Identifying Autism Spectrum Disorder Based on Indi…

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Autism Spectrum Disorder (ASD) has been emerging as a growing public health threat. Early diagnosis of ASD is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and…

计算机视觉与模式识别 · 计算机科学 2024-05-06 Zhuowen Yin , Xinyao Ding , Xin Zhang , Zhengwang Wu , Li Wang , Xiangmin Xu , Gang Li

Individuals with Autism Spectrum Disorder (ASD) often experience challenges in health, communication, and sensory processing; therefore, early diagnosis is necessary for proper treatment and care. In this work, we consider the problem of…

计算机视觉与模式识别 · 计算机科学 2024-04-02 M. Serna-Aguilera , X. B. Nguyen , A. Singh , L. Rockers , S. Park , L. Neely , H. Seo , K. Luu

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by varied social cognitive challenges and repetitive behavioral patterns. Identifying reliable brain imaging-based biomarkers for ASD has been a persistent…

Autism Spectrum Disorder (ASD) is one neuro developmental disorder that is now widespread in the world. ASD persists throughout the life of an individual, impacting the way they behave and communicate, resulting to notable deficits…

计算机视觉与模式识别 · 计算机科学 2023-03-23 Godfrin Ismail , Kenneth Chesoli , Golda Moni , Kinyua Gikunda

Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) techniques can aid physicians to apply automatic diagnosis and…

Currently, every 1 in 54 children have been diagnosed with Autism Spectrum Disorder (ASD), which is 178% higher than it was in 2000. An early diagnosis and treatment can significantly increase the chances of going off the spectrum and…

计算机视觉与模式识别 · 计算机科学 2021-04-05 Spencer He , Ryan Liu

Increasing the volume of training data can enable the auxiliary diagnostic algorithms for Autism Spectrum Disorder (ASD) to learn more accurate and stable models. However, due to the significant heterogeneity and domain shift in rs-fMRI…

神经元与认知 · 定量生物学 2025-07-11 Yiqian Luo , Qiurong Chen , Fali Li , Peng Xu , Yangsong Zhang

Objective. The paper investigates the presence of autism using the functional brain connectivity measures derived from electro-encephalogram (EEG) of children during face perception tasks. Approach. Phase synchronized patterns from…

Autism spectrum disorder (ASD) is a complex neurodevelopmental syndrome. Early diagnosis and precise treatment are essential for ASD patients. Although researchers have built many analytical models, there has been limited progress in…

神经元与认知 · 定量生物学 2018-10-30 Juntang Zhuang , Nicha C. Dvornek , Xiaoxiao Li , Pamela Ventola , James S. Duncan

In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, arousal, and valence. Our system classifies ASD using…

计算机视觉与模式识别 · 计算机科学 2019-04-09 Beibin Li , Sachin Mehta , Deepali Aneja , Claire Foster , Pamela Ventola , Frederick Shic , Linda Shapiro

Functional magnetic resonance imaging (fMRI) has become instrumental in researching brain function. One application of fMRI is investigating potential neural features that distinguish people with autism spectrum disorder (ASD) from healthy…

图像与视频处理 · 电气工程与系统科学 2024-12-19 Sjir J. C. Schielen , Jesper Pilmeyer , Albert P. Aldenkamp , Danny Ruijters , Svitlana Zinger

Autism spectrum disorder (ASD) affects the brain connectivity at different levels. Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging (MRI) remains very challenging to machine learning diagnostic…

机器学习 · 计算机科学 2020-04-29 Ismail Bilgen , Goktug Guvercin , Islem Rekik

Deep learning methods are increasingly being used with neuroimaging data like structural and function magnetic resonance imaging (MRI) to predict the diagnosis of neuropsychiatric and neurological disorders. For psychiatric disorders in…

神经元与认知 · 定量生物学 2019-07-03 Ahmed El Gazzar , Leonardo Cerliani , Guido van Wingen , Rajat Mani Thomas

While graph convolution based methods have become the de-facto standard for graph representation learning, their applications to disease prediction tasks remain quite limited, particularly in the classification of neurodevelopmental and…

计算机视觉与模式识别 · 计算机科学 2023-11-17 Ibrahim Salim , A. Ben Hamza

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that encompasses a wide variety of symptoms and degrees of impairment, which makes the diagnosis and treatment challenging. Functional magnetic resonance imaging (fMRI) has…

计算机视觉与模式识别 · 计算机科学 2024-09-20 Yinchi Zhou , Peiyu Duan , Yuexi Du , Nicha C. Dvornek

Autism, also known as Autism Spectrum Disorder (or ASD), is a neurological disorder. Its main symptoms include difficulty in (verbal and/or non-verbal) communication, and rigid/repetitive behavior. These symptoms are often indistinguishable…

计算机视觉与模式识别 · 计算机科学 2023-07-18 Asha Rani , Pankaj Yadav , Yashaswi Verma

These days, computational diagnosis strategies of neuropsychiatric disorders are gaining attention day by day. It's critical to determine the brain's functional connectivity based on Functional-Magnetic-Resonance-Imaging(fMRI) to diagnose…

计算机视觉与模式识别 · 计算机科学 2022-05-05 Sartaj Ahmed Salman , Zhichao Lian , Marva Saleem , Yuduo Zhang

Autism Spectrum Disorder (ASD) is a chronic neurodevelopmental condition characterized by repetitive behaviors and impairments in social and communication skills. Despite the clear manifestation of these symptoms, many individuals with ASD…

机器学习 · 计算机科学 2026-01-27 Aneesh Panchal , Kainat Khan , Rahul Katarya

Autism Spectrum Disorders (ASDs) are often associated with specific atypical postural or motor behaviors, of which Stereotypical Motor Movements (SMMs) have a specific visibility. While the identification and the quantification of SMM…

神经与进化计算 · 计算机科学 2016-06-08 Nastaran Mohammadian Rad , Andrea Bizzego , Seyed Mostafa Kia , Giuseppe Jurman , Paola Venuti , Cesare Furlanello

Autism Spectrum Disorder (ASD) is often underdiagnosed in females due to gender-specific symptom differences overlooked by conventional diagnostics. This study evaluates machine learning models, particularly Random Forest and convolutional…

计算机视觉与模式识别 · 计算机科学 2024-11-12 Mohammed Aledhari , Mohamed Rahouti , Ali Alfatemi