Related papers: Federated Anomaly Detection for Early-Stage Diagno…
Autism Spectrum Disorder (ASD) is a neuro-developmental syndrome resulting from alterations in the embryological brain before birth. This disorder distinguishes its patients by special socially restricted and repetitive behavior in addition…
Automated recognition of autistic behaviors in children is essential for early intervention and objective clinical assessment. However, the development of robust models is severely hindered by strict privacy regulations (e.g., HIPAA) and…
Mental disorders such as Autism Spectrum Disorders (ASD) are heterogeneous disorders that are notoriously difficult to diagnose, especially in children. The current psychiatric diagnostic process is based purely on the behavioural…
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…
The emergence of federated learning (FL) presents a promising approach to leverage decentralized data while preserving privacy. Furthermore, the combination of FL and anomaly detection is particularly compelling because it allows for…
Autistic Spectrum Disorder (ASD) is a neurological disease characterized by difficulties with social interaction, communication, and repetitive activities. While its primary origin lies in genetics, early detection is crucial, and…
The path to an autism diagnosis can be long and difficult, and delays can have serious consequences. Artificial intelligence can completely change the way autism is diagnosed, especially when it comes to situations where it is difficult to…
Federated learning (FL) is proving to be one of the most promising paradigms for leveraging distributed resources, enabling a set of clients to collaboratively train a machine learning model while keeping the data decentralized. The…
Autism Spectrum Disorder (ASD), which is a neuro development disorder, is often accompanied by sensory issues such an over sensitivity or under sensitivity to sounds and smells or touch. Although its main cause is genetics in nature, early…
Federated learning (FL) is an effective paradigm for distributed environments such as the Internet of Things (IoT), where data from diverse devices with varying functionalities remains localized while contributing to a shared global model.…
Autism Spectrum Disorder(ASD) is a set of neurodevelopmental conditions that affect patients' social abilities. In recent years, many studies have employed deep learning to diagnose this brain dysfunction through functional MRI (fMRI).…
In the evolving landscape of Federated Learning (FL), the challenge of ensuring data integrity against poisoning attacks is paramount, particularly for applications demanding stringent privacy preservation. Traditional anomaly detection…
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…
Federated Learning (FL) is transforming the ML training ecosystem from a centralized over-the-cloud setting to distributed training over edge devices in order to strengthen data privacy. An essential but rarely studied challenge in FL is…
In Federated Learning (FL), anomaly detection (AD) is a challenging task due to the decentralized nature of data and the presence of non-IID data distributions. This study introduces a novel federated threshold calculation method that…
Autism Spectrum Disorder (ASD) is a severe neuropsychiatric disorder that affects intellectual development, social behavior, and facial features, and the number of cases is still significantly increasing. Due to the variety of symptoms ASD…
Federated Learning (FL) is an advanced distributed machine learning approach, that protects the privacy of each vehicle by allowing the model to be trained on multiple devices simultaneously without the need to upload all data to a road…
Research has increasingly explored the application of artificial intelligence (AI) and machine learning (ML) within the mental health domain to enhance both patient care and healthcare provider efficiency. Given that mental health…
Diagnosing Autism Spectrum Disorder (ASD) is a challenging problem, and is based purely on behavioral descriptions of symptomology (DSM-5/ICD-10), and requires informants to observe children with disorder across different settings (e.g.…
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…