Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 88 - 103
Published: Dec. 7, 2024
Language: Английский
Military Medical Research, Journal Year: 2023, Volume and Issue: 10(1)
Published: Dec. 19, 2023
Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity dynamic changes in neural signals, EEG has aroused much interest scientific research medical fields. This article reviews the types of multiple signal analysis methods, application relevant methods neuroscience field diagnosing neurological diseases. First, three including time-invariant EEG, accurate event-related random are introduced. Second, five main directions analysis, power spectrum time-frequency connectivity source localization machine learning described section, along with different sub-methods effect evaluations solving same problem. Finally, scenarios emphasized, advantages disadvantages similar distinguished. expected assist researchers selecting suitable based on their objectives, provide references subsequent research, summarize current issues prospects future.
Language: Английский
Citations
58
Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(2), P. 550 - 550
Published: Jan. 16, 2025
The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding the brain, unlocking new possibilities in research, diagnosis, therapy. This review explores how AI’s cutting-edge algorithms—ranging from deep learning to neuromorphic computing—are revolutionizing by enabling analysis complex neural datasets, neuroimaging electrophysiology genomic profiling. These advancements are transforming early detection neurological disorders, enhancing brain–computer interfaces, driving personalized medicine, paving way for more precise adaptive treatments. Beyond applications, itself has inspired AI innovations, with architectures brain-like processes shaping advances algorithms explainable models. bidirectional exchange fueled breakthroughs such as dynamic connectivity mapping, real-time decoding, closed-loop systems that adaptively respond states. However, challenges persist, including issues data integration, ethical considerations, “black-box” nature many systems, underscoring need transparent, equitable, interdisciplinary approaches. By synthesizing latest identifying future opportunities, this charts a path forward integration neuroscience. From harnessing multimodal cognitive augmentation, fusion these fields not just brain science, it reimagining human potential. partnership promises where mysteries unlocked, offering unprecedented healthcare, technology, beyond.
Language: Английский
Citations
11
Nonlinear Dynamics, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 6, 2025
Language: Английский
Citations
2
Brain‐X, Journal Year: 2024, Volume and Issue: 2(2)
Published: April 26, 2024
Abstract This comprehensive review aims to clarify the growing impact of Transformer‐based models in fields neuroscience, neurology, and psychiatry. Originally developed as a solution for analyzing sequential data, Transformer architecture has evolved effectively capture complex spatiotemporal relationships long‐range dependencies that are common biomedical data. Its adaptability effectiveness deciphering intricate patterns within medical studies have established it key tool advancing our understanding neural functions disorders, representing significant departure from traditional computational methods. The begins by introducing structure principles architectures. It then explores their applicability, ranging disease diagnosis prognosis evaluation cognitive processes decoding. specific design modifications tailored these applications subsequent on performance also discussed. We conclude providing assessment recent advancements, prevailing challenges, future directions, highlighting shift neuroscientific research clinical practice towards an artificial intelligence‐centric paradigm, particularly given prominence most successful large pre‐trained models. serves informative reference researchers, clinicians, professionals who interested harnessing transformative potential
Language: Английский
Citations
7
Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 173, P. 108331 - 108331
Published: March 21, 2024
Language: Английский
Citations
4
Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 104, P. 107543 - 107543
Published: Jan. 24, 2025
Citations
0
Advances in Psychiatry and Behavioral Health, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 1, 2025
Language: Английский
Citations
0
Deleted Journal, Journal Year: 2025, Volume and Issue: unknown
Published: March 5, 2025
Abstract The complex relationship between emotions and mental health demands a more comprehensive theoretical framework that can capture its dynamic multifaceted nature. This perspective article proposes novel trimodal approach conceptually integrates three complementary methodologies: Ecological Momentary Assessment, physiological measurements, Speech Emotion Recognition. By adopting dynamical system perspective, we argue the convergence of these methodologies could provide unprecedented insights into emotional dynamics in research practice. We discuss how this transform our understanding by simultaneously capturing subjective experiences, responses, linguistic patterns naturalistic settings. proposed integration offers conceptual foundation for developing sophisticated approaches to monitoring intervention. explore implications, methodological considerations, potential future directions integrated highlighting promise advancing both clinical practice health.
Language: Английский
Citations
0
Mathematical Biosciences & Engineering, Journal Year: 2024, Volume and Issue: 21(2), P. 3016 - 3036
Published: Jan. 1, 2024
<abstract><p>Surface defect detection is of great significance as a tool to ensure the quality steel pipes. The surface defects pipes are charactered by insufficient texture, high similarity between different types defects, large size differences, and proportions small targets, posing challenges algorithms. To overcome above issues, we propose novel pipe method based on YOLO framework. First, for problem low rate caused texture among pipes, new backbone block proposed. By increasing high-order spatial interaction enhancing capture internal correlations data features, feature information similar extracted, thereby alleviating false rate. Second, enhance performance neck fusing multiple accuracy improved. Third, causing differences in regression loss function that considers aspect ratio scale proposed, focal introduced further solve sample imbalance datasets. experimental results show proposed can effectively improve detection.</p></abstract>
Language: Английский
Citations
3
Diagnostics, Journal Year: 2024, Volume and Issue: 14(9), P. 920 - 920
Published: April 28, 2024
Early pregnancy loss (EPL) is a prevalent health concern with significant implications globally for gestational health. This research leverages machine learning to enhance the prediction of EPL and differentiate between typical pregnancies those at elevated risk during initial trimester. We employed different methodologies, from conventional models more advanced ones such as deep multilayer perceptron models. Results both classical were evaluated using confusion matrices, cross-validation techniques, analysis feature significance obtain correct decisions among algorithmic strategies on early vitamin D serum connection in The results demonstrated that powerful tool accurately predicting EPL, outperforming ones. Linear discriminant quadratic algorithms shown have 98 % accuracy outcomes. Key determinants identified, including levels maternal D. In addition, prior outcomes age are crucial factors study's findings highlight potential enhancing predictions related can contribute improved mothers infants.
Language: Английский
Citations
2