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Sá RODS, Michelassi GDC, Butrico DDS, Franco FDO, Sumiya FM, Portolese J, Brentani H, Nunes FLS, Machado-Lima A. Enhancing ensemble classifiers utilizing gaze tracking data for autism spectrum disorder diagnosis. Comput Biol Med 2024; 182:109184. [PMID: 39353297 DOI: 10.1016/j.compbiomed.2024.109184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 08/28/2024] [Accepted: 09/20/2024] [Indexed: 10/04/2024]
Abstract
PROBLEM Diagnosing Autism Spectrum Disorder (ASD) remains a significant challenge, especially in regions where access to specialists is limited. Computer-based approaches offer a promising solution to make diagnosis more accessible. Eye tracking has emerged as a valuable technique in aiding the diagnosis of ASD. Typically, individuals' gaze patterns are monitored while they view videos designed according to established paradigms. In a previous study, we developed a method to classify individuals as having ASD or Typical Development (TD) by processing eye-tracking data using Random Forest ensembles, with a focus on a paradigm known as joint attention. AIM This article aims to enhance our previous work by evaluating alternative algorithms and ensemble strategies, with a particular emphasis on the role of anticipation features in diagnosis. METHODS Utilizing stimuli based on joint attention and the concept of "floating regions of interest" from our earlier research, we identified features that indicate gaze anticipation or delay. We then tested seven class balancing strategies, applied seven dimensionality reduction algorithms, and combined them with five different classifier induction algorithms. Finally, we employed the stacking technique to construct an ensemble model. RESULTS Our findings showed a significant improvement, achieving an F1-score of 95.5%, compared to the 82% F1-score from our previous work, through the use of a heterogeneous stacking meta-classifier composed of diverse induction algorithms. CONCLUSION While there remains an opportunity to explore new algorithms and features, the approach proposed in this article has the potential to be applied in clinical practice, contributing to increased accessibility to ASD diagnosis.
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Affiliation(s)
- Rafaela Oliveira da Silva Sá
- School of Arts, Sciences and Humanities (EACH) of the University of Sao Paulo (USP), Rua Arlindo Béttio, 1000 - Ermelino Matarazzo, São Paulo, 03828-000, São Paulo, Brazil.
| | - Gabriel de Castro Michelassi
- School of Arts, Sciences and Humanities (EACH) of the University of Sao Paulo (USP), Rua Arlindo Béttio, 1000 - Ermelino Matarazzo, São Paulo, 03828-000, São Paulo, Brazil.
| | - Diego Dos Santos Butrico
- Department of Psychiatry, University of Sao Paulo's School of Medicine (FMUSP), Rua Doutor Ovídio Pires de Campos, 785 - Cerqueira César, São Paulo, 05403-010, São Paulo, Brazil.
| | - Felipe de Oliveira Franco
- Department of Psychiatry, University of Sao Paulo's School of Medicine (FMUSP), Rua Doutor Ovídio Pires de Campos, 785 - Cerqueira César, São Paulo, 05403-010, São Paulo, Brazil.
| | - Fernando Mitsuo Sumiya
- Department of Psychiatry, University of Sao Paulo's School of Medicine (FMUSP), Rua Doutor Ovídio Pires de Campos, 785 - Cerqueira César, São Paulo, 05403-010, São Paulo, Brazil.
| | - Joana Portolese
- Department of Psychiatry, University of Sao Paulo's School of Medicine (FMUSP), Rua Doutor Ovídio Pires de Campos, 785 - Cerqueira César, São Paulo, 05403-010, São Paulo, Brazil.
| | - Helena Brentani
- Department of Psychiatry, University of Sao Paulo's School of Medicine (FMUSP), Rua Doutor Ovídio Pires de Campos, 785 - Cerqueira César, São Paulo, 05403-010, São Paulo, Brazil.
| | - Fátima L S Nunes
- School of Arts, Sciences and Humanities (EACH) of the University of Sao Paulo (USP), Rua Arlindo Béttio, 1000 - Ermelino Matarazzo, São Paulo, 03828-000, São Paulo, Brazil.
| | - Ariane Machado-Lima
- School of Arts, Sciences and Humanities (EACH) of the University of Sao Paulo (USP), Rua Arlindo Béttio, 1000 - Ermelino Matarazzo, São Paulo, 03828-000, São Paulo, Brazil.
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Khougar A, Baba Ahmadi P, Ranjbar H, Ahadi M, Ahadi P. Exploring the varied manifestations of structural violence in the lives of children on the autism spectrum and their families: a qualitative longitudinal study in Kurdistan, Iran. Int J Equity Health 2023; 22:263. [PMID: 38110989 PMCID: PMC10729435 DOI: 10.1186/s12939-023-02078-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 12/05/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND There are many dimensions regarding autism that are closely connected to social structures, policies, and power dynamics, silently impacting the well-being of individuals within the autism spectrum. This research aims to explore these overlooked aspects using a theoretical framework called "structural violence." METHODS The study was conducted in Kurdistan, Iran, and a qualitative longitudinal approach was chosen. A purposive sampling method was employed to select the participants, with 11 parents taking part. The study data comprised 29 interviews using a topic guide conducted over a span of 2 years. Thematic analysis and a matrix-based approach were utilized for data analysis. To enhance the scientific rigor of this research, four criteria, including Guba and Lincoln's principles, were implemented to ensure methodological accuracy. RESULTS The research findings highlight four primary forms through which structural violence impacts children on the autism spectrum and their families: access to healthcare, geographic disparities, awareness and stigma, and poverty and financial burden. Additionally, the study identified 11 subthemes related to structural violence in the context of autism and families. CONCLUSIONS We illustrated how structural forces create barriers to accessing adequate healthcare services, exacerbate discrimination based on ethnicity and geography, perpetuate stigma, and contribute to poverty and the inability to meet basic needs. These factors not only worsen health issues but also deepen existing disparities in healthcare access and outcomes for children on the autism spectrum and families. We emphasize the urgent need for systemic changes to address these issues. It is essential to promote public awareness, provide better access to health and support services, and address economic and political factors that contribute to these inequalities.
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Affiliation(s)
- Ansar Khougar
- Primary Health Care Center, Iran University of Medical Science, Shahryar, Iran
| | - Paria Baba Ahmadi
- Student Research Committee, School of Medicine, Shirza University of Medical Sciences, Shiraz, Iran
| | - Hadi Ranjbar
- Mental Health Research Center, Iran University of Medical Science, Tehran, Iran
| | - Mahsa Ahadi
- Student Research Committee, School of Medicine, Shirza University of Medical Sciences, Shiraz, Iran
| | - Parisa Ahadi
- Department of Pharmacy, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran.
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Nair AS, Priya RS, Rajagopal P, Pradeepa C, Senthil R, Dhanalakshmi S, Lai KW, Wu X, Zuo X. A case study on the effect of light and colors in the built environment on autistic children's behavior. Front Psychiatry 2022; 13:1042641. [PMID: 36532166 PMCID: PMC9748440 DOI: 10.3389/fpsyt.2022.1042641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 11/14/2022] [Indexed: 12/05/2022] Open
Abstract
Background The importance of strategies and services by caregivers and family members substantially impact the psychological and emotional wellbeing of autistic children. The rapid research developments in clinical and non-clinical methods benefit the features of autistic children. Among various internal and external factors, the influence of the built environment also impacts the characteristics of autistic children. This study investigates primarily the psychological effect of light and colors on the mood and behavior of autistic children to identify the most favorable and preferred indoor lights and color shades. Methods A questionnaire survey was conducted at an autism center among autistic children and their parents. This study included autistic children aged between 6 and 16 (45 males, 42 females, mean age 8.7 years, standard deviation 2.3). Eighty-seven participants were involved in the survey to determine the sensory perceptions, intolerance, preferences, and sensitivities of children with an autism spectrum disorder toward colors and lighting. The margin of error at the statistical analysis's 95% confidence level is ± 0.481. Results As per this case report, the children have various color preferences and respond differently to different shades. Different hues have varying effects on autistic children, with many neutral tones and mellow shades proven to be autistic-friendly with their calming and soothing effect, while bright, bold, and intense colors are refreshing and stimulating. The stimulus of bright-lighting causes behavioral changes in autistic children prone to light sensitivity. Conclusion The insights gained from this interaction with parents and caretakers of autistic children could be helpful for designers to incorporate specific autistic-friendly design elements that make productive interior spaces. A complete understanding of the effect of factors like color and lighting on the learning ability and engagement of autistic children in an indoor environment is essential for designers and clinicians. The main findings of this study could be helpful for a designer and clinicians to address designing an autism-friendly built environment with a color palette and lighting scheme conducive to their wellbeing and to maximize their cognitive functioning.
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Affiliation(s)
- Ashwini Sunil Nair
- School of Architecture and Interior Design, SRM Institute of Science and Technology, Chennai, India
| | | | - Prashanthini Rajagopal
- School of Architecture and Interior Design, SRM Institute of Science and Technology, Chennai, India
| | - Chandramouli Pradeepa
- School of Architecture and Interior Design, SRM Institute of Science and Technology, Chennai, India
| | - Ramalingam Senthil
- Department of Mechanical Engineering, SRM Institute of Science and Technology, Chennai, India
| | - Samiappan Dhanalakshmi
- Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai, India
| | - Khin Wee Lai
- Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Xiang Wu
- School of Medical Information and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Xiaowei Zuo
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
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