Inteligencia artificial en el estudio del uso de escaneo cerebral en la implementación en usuarios neurodivergentes

• Mateo Dwyer ^[1]
  1. [1] Universidad Autónoma de Querétaro

     Universidad Autónoma de Querétaro

     México

     
• Localización: RISTI: Revista Ibérica de Sistemas e Tecnologias de Informação, ISSN-e 1646-9895, Nº. 54, 2024, págs. 39-51
• Idioma: español
• DOI: 10.17013/risti.54.39-51
• Enlaces
  • Texto completo
• Resumen
  • español

    La salud mental en general es un tema que ha ganado mucha relevancia e importancia en los últimos años. Pero un elemento central de ésta es el tema de trastornos mentales, y el diagnóstico de ellos. Por mucho tiempo, el método estándar usado para este proceso ha sido lento y costoso. Sin embargo, con nuevas tecnologías como son la inteligencia artificial y el escaneo cerebral hay posibilidad de una detección más rápida, sencilla, y objetiva de estos trastornos, incluido a edades más tempranas. El objetivo de este estudio es verificar la eficacia del reconocimiento de patrones eléctricos cerebrales mediante la inteligencia artificial en el uso médico psicológico, utilizando opiniones profesionales para determinar su factibilidad. El análisis fue cuanti-cualitativo, y se encontró que estas herramientas probablemente serán indispensables para esta área en el futuro cercano, siempre y cuando se le de un enfoque particular a su desarrollo.

  • English

    Mental health in general is a subject that has become more and more relevant in the past years. But a central element to this subject is mental disorders, and their diagnosis. For a long time, the standard method used for this project has been lengthy and expensive. However, with new technologies such as artificial intelligence and brainwave scanning there is a chance for faster, simpler, and more objective detection of these disorders, including at ages too young for the current method. The objective of this study is to verify the efficiency of the recognizement of brainwave patterns using artificial intelligence in the psychology-medicinal field, using professional opinions to determine its feasibility. The analysis was quantiqualitative, and it was found that these tools will most likely be indispensable for this field in the near future, as long as they are given the proper development.

• Referencias bibliográficas
  • Abd-Alrazaq, A., Alhuwail, D., Schneider, J., et al. (2022). The performance of artificial intelligence-driven technologies in diagnosing...
  • Ahmad, N., Rehman, M., El Hassan, H., et al. (2022). An efficient machine learning-based feature optimization model for the detection of dyslexia....
  • Albajara Sáenz, A., Villemonteix, T., & Massat, I. (2019). Structural and functional neuroimaging in attention-deficit/hyperactivity disorder....
  • Anchana, V., & Biju, K. (2023). Comparative study of detection of ADHD using EEG signals. 2023 International Conference on Control, Communication...
  • Arji, G., Erfannia, L., Aliarezaei, A., et al. (2023). A systematic literature review and analysis of deep learning algorithms in mental disorders....
  • Bakhtyari, M., & Mirzaei, S. (2022). ADHD detection using dynamic connectivity patterns of EEG data and ConvLSTM with attention framework....
  • Barua, P., Dogan, S., Baygin, M., et al. (2022). TMP19: A novel ternary motif pattern-based ADHD detection model using EEG signals. Diagnostics....
  • Barua, P., Vicnesh, J., Gururajan, R., et al. (2022). Artificial intelligence enabled personalised assistive tools to enhance education of...
  • Bayram, M., Özer, I., & Termurtas, F. (2021). Deep learning methods for autism spectrum disorder diagnosis based on fMRI images. Sakarya...
  • Bouallegue, G., Djemal, R., Alshbeili, S., et al. (2020). A dynamic filtering DF-RNN deep-learning-based approach for EEG-based neurological...
  • Boughattas, N., & Jabnoun, H. (2022). Autism spectrum disorder (ASD) detection using machine learning algorithms. In Lecture Notes in...
  • Byrne, D., Gorman, K., Twomey, E., et al. (2021). Yield of diagnosis in MRI brain imaging in children with autism spectrum disorder. Developmental...
  • Chen, Z., Kulkarni, P., Glatzer-Levy, I., et al. (2022). Modern views of machine learning for precision psychiatry. Patterns. https://doi.org/10.1016/j.patter.2022.100602
  • Farooq, M., Tehseen, R., Sabir, M., et al. (2023). Detection of autism spectrum disorder (ASD) in children and adults using machine learning....
  • Farooqui, Q., & Rahman, M. (2022). Autism spectrum disorder (ASD) diagnosis and reinforcement by machine learning and neural networks....
  • Feng, X., Hu, M., & Guo, W. (2022). Application of artificial intelligence in mental health and mental illnesses. 2022 3rd International...
  • Firouzabadi, F., Ramenzanpour, S., Firouzabadi, M., et al. (2022). Neuroimaging in attention-deficit/hyperactivity disorder: Recent advances....
  • Gupte, N., Patel, M., Pen, T., et al. (2023). Early detection of ADHD and dyslexia from EEG signals. 2023 IEEE 8th International Conference...
  • Heinz, M., Bhattacharya, S., Trudeau, B., et al. (2023). Testing domain knowledge and risk of bias of a large-scale general artificial intelligence...
  • Helmy, E., Elnakib, A., Elnakieb, Y., et al. (2023). Role of artificial intelligence for autism diagnosis using DTI and fMRI: A survey. Biomedicines....
  • Hilal, A., Issaoui, I., Obayya, M., et al. (2022). Modeling of explainable artificial intelligence for biomedical mental disorder diagnosis....
  • Huse, S., Acharaya, S., Shukla, S., et al. (2022). Computer-aided detection and diagnosis of neurological disorder. Cureus. https://doi.org/10.7759/cureus.28032
  • Jain, P., & Quadri, S. (2021). Emerging role of intelligent techniques for effective detection and prediction of mental disorders. Lecture...
  • Jatain, A., & Vashisht, P. (2023). A novel approach for diagnosing neuro-developmental disorders using artificial intelligence. Dialnet. ...
  • Joy, R., George, S., Rajan, A., et al. (2022). Detection and classification of ADHD from EEG signals using tunable Q-factor wavelet transform....
  • Kaisar, S. (2020). Developmental dyslexia detection using machine learning techniques: A survey. ICT Express. https://doi.org/10.1016/j.icte.2020.05.006
  • Khare, S., Gaikwad, N., & Bajaj, V. (2022). VHERS: A novel variational mode decomposition and Hilbert transform-based EEG rhythm separation...
  • Khodatars, M., Shoebi, A., Sadeghi, D., et al. (2021). Neuroimaging database and machine learning-based analysis for neurological disorders....
  • Kister, K., Laskowski, J., Makarewicz, A., et al. (2023). Application of artificial intelligence tools in diagnosis and treatment of mental...
  • Kresnia, G., & Parikesit, A. (2022). Use of artificial intelligence in the diagnostics of autism spectrum disorder. Cermin Dunia Kedokteran....
  • Kusano, K., Tashiro, T., Matsubara, T., et al. (2019). Deep generative state-space modeling of FMRI images for psychiatric disorder diagnosis....
  • Loh, H., Ooi, C., Barua, P., et al. (2022). Automated detection of ADHD: Current trends and future perspective. Computers in Biology and Medicine....
  • Maniruzzman, M., Hasan, M., Asai, N., et al. (2023). Optimal channels and features selection based ADHD detection from EEG signal using statistical...
  • Maniruzzman, M., Shin, J., Hasan, M., et al. (2022). Efficient feature selection and machine learning based ADHD detection using EEG signal....
  • Martinhago, F., Lavagnino, N., & Folguera, G. (2019). Factores de riesgo y bases genéticas: El caso del trastorno por déficit de atención...
  • Murugappan, M., & Yuvaraj, R. (2022). Biomedical signals based computer-aided diagnosis for neurological disorders. Mendeley. https://doi.org/10.1007/978-3-030-97845-7
  • Nash, C., Nair, R., & Naqvi, S. (2022). Machine learning and ADHD mental health detection - A short survey. 2022 25th International Conference...
  • Nogay, H., & Adeli, H. (2020). Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging. Reviews...
  • Rabelo-da-Ponte, F., de Azevedo Cardoso, T., Kapczinski, F., et al. (2023). The use of artificial intelligence to identify trajectories of...
  • Raju, N., Madhavi, K., Sravan Kumar, G., et al. (2019). Prognostication of autism spectrum disorder (ASD) using supervised machine learning...
  • Rivera, M., Teruel, M., Maté, A., et al. (2022). Diagnosis and prognosis of mental disorders by means of EEG and deep learning: A systematic...
  • Roy, Y., Banville, H., Alburquerque, I., et al. (2019). Deep learning-based electroencephalography analysis: A systematic review. https://doi.org/10.1088/1741-2552/ab260c
  • Sadeghi, D., Shoeibi, A., Ghassemi, N., et al. (2022). An overview of artificial intelligence techniques for diagnosis of schizophrenia based...
  • Sadiq, M., Akbari, H., Siuly, S., et al. (2021). A novel computer-aided diagnosis framework for EEG-based identification of neural diseases....
  • Samy Helmy, A., & Samy Helmy, B. (2022). Role of artificial intelligence in mental wellbeing: Opportunities and challenges. Journal of...
  • Son, H., Lee, D., Joung, Y., et al. (2021). A novel approach to diagnose ADHD using virtual reality. International Journal of Web Information...
  • Song, J., Yoon, N., Jang, S., et al. (2020). Neuroimaging-based deep learning in autism spectrum disorder and attention-deficit/hyperactivity...
  • Sun, J., Dong, Q., Wang, S., et al. (2023). Artificial intelligence in psychiatry research, diagnosis, and therapy. Asian Journal of Psychiatry. ...
  • Tachmazidis, I., Chen, T., Adamou, M., et al. (2021). A hybrid AI approach for supporting clinical diagnosis of attention deficit hyperactivity...
  • Tanwar, P., & Sharma, A. (2021). Machine learning techniques for autism spectrum disorder (ASD) detection. International Journal of Forensic...
  • Tutun, S., Johnson, M., Ahmed, A., et al. (2023). An AI-based decision support system for predicting mental health disorders. Information...
  • Velarde-Incháustegui, M., Ignacio-Espíritu, M., & Cárdenas-Soza, A. (2021). Diagnóstico de Trastorno del Espectro Autista-TEA, adaptándonos...
  • Venkatasubramanian, G. (2022). Machine learning-based diagnosis of autism spectrum disorder using brain imaging. iScience Notes. https://doi.org/10.22580/iSciNoteJ7.7.4
  • Vishal, V., Singh, A., Jinila, Y., et al. (2022). A comparative analysis of prediction of autism spectrum disorder (ASD) using machine learning....
  • Wright, K. (2021). Brain imaging for autism diagnosis. Physics. https://doi.org/10.1103/physics.14.44
  • Yadav, K., & Hasija, Y. (2022). Artificial intelligence and technological development in behavioral and mental healthcare. 2022 International...
  • Yan, W., Ruan, Q., & Jiang, K. (2022). Challenges for artificial intelligence in recognizing mental disorders. Diagnostics. https://doi.org/10.3390/diagnostics13010002
  • Yin, W., Li, L., & Wu, F. (2022). Deep learning for brain disorder diagnosis based on fMRI images. Neurocomputing. https://doi.org/10.1016/j.neucom.2020.05.113
  • Yin, W., Mostafa, S., & Wu, F. (2021). Diagnosis of autism spectrum disorder based on functional brain networks with deep learning. Journal...
  • Zahia, S., Garcia-Zapirain, B., Saralegui, I., et al. (2020). Dyslexia detection using 3D convolutional neural networks and functional magnetic...
  • Zhang, L., Wang, M., Liu, M., et al. (2020). A survey on deep learning for neuroimaging-based brain disorder analysis. Frontiers in Neuroscience....
  • Zhang, W., Yang, C., Cao, Z., et al. (2023). Detecting individuals with severe mental illness using artificial intelligence applied to magnetic...
  • Zhang, X., Wang, R., Sharma, A., et al. (2021). Artificial intelligence in cognitive psychology: Influence of literature based on artificial...
  • Zhou, S., Zhao, J., & Zhang, L. (2022). Application of artificial intelligence on psychological interventions and diagnosis: An overview....