Artificial intelligence-based approaches for improving the diagnosis, triage, and prioritization of autism spectrum disorder: a systematic review of current trends and …
The artificial intelligence (AI) trend to embrace Autism Spectrum Disorder (ASD) has
dramatically transformed the landscape of medical diagnosis. People often exhibit fear and …
dramatically transformed the landscape of medical diagnosis. People often exhibit fear and …
A comprehensive review of deep learning power in steady-state visual evoked potentials
Brain–computer interfacing (BCI) research, fueled by deep learning, integrates insights from
diverse domains. A notable focus is on steady-state visual evoked potential (SSVEP) in BCI …
diverse domains. A notable focus is on steady-state visual evoked potential (SSVEP) in BCI …
[HTML][HTML] Fuzzy decision-making framework for explainable golden multi-machine learning models for real-time adversarial attack detection in Vehicular Ad-hoc …
This paper addresses various issues in the literature concerning adversarial attack detection
in Vehicular Ad-hoc Networks (VANETs). These issues include the failure to consider both …
in Vehicular Ad-hoc Networks (VANETs). These issues include the failure to consider both …
[HTML][HTML] Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model
Developing a comprehensive data-driven strategy for evaluating the organisational culture
in companies to foster digital innovation involves a multi-criteria decision-making (MCDM) …
in companies to foster digital innovation involves a multi-criteria decision-making (MCDM) …
A trustworthy and explainable framework for benchmarking hybrid deep learning models based on chest X-ray analysis in CAD systems
Evaluating the trustworthiness of deep learning-based computer-aided diagnosis (CAD)
systems is challenging. There is a need to optimize trust and performance in model …
systems is challenging. There is a need to optimize trust and performance in model …
CWBCM method to determine the importance of classification performance evaluation criteria in machine learning: Case studies of COVID-19, Diabetes, and Thyroid …
M Parishani, M Rasti-Barzoki - Omega, 2024 - Elsevier
Problems with multiple conflicting criteria are usually modeled by the methods proposed in
the field of Multi-Criteria Decision Making (MCDM). In MCDM, one of the most important …
the field of Multi-Criteria Decision Making (MCDM). In MCDM, one of the most important …
Optimal Time Window Selection in the Wavelet Signal Domain for Brain–Computer Interfaces in Wheelchair Steering Control
ZT Al-Qaysi, MS Suzani… - … Data Science and …, 2024 - mesopotamian.press
Background and objective: Principally, the procedure of pattern recognition in terms of
segmentation plays a significant role in a BCI-based wheelchair control system for avoiding …
segmentation plays a significant role in a BCI-based wheelchair control system for avoiding …
Development of hybrid feature learner model integrating FDOSM for golden subject identification in motor imagery
Brain-computer interfaces (BCIs) based on motor imagery (MI) face challenges due to the
complex nature of brain activity, nonstationary and high-dimensional properties, and …
complex nature of brain activity, nonstationary and high-dimensional properties, and …
[PDF][PDF] Hybrid Model for Motor Imagery Biometric Identification
RA Aljanabi, ZT Al-Qaysi, MA Ahmed… - Iraqi Journal For Computer …, 2024 - iasj.net
Biometric systems are a continuously evolving and promising technological domain that can
be used in automatic systems for the unique and efficient identification and authentication of …
be used in automatic systems for the unique and efficient identification and authentication of …
Towards trustworthy myopia detection: integration methodology of deep learning approach, XAI visualization, and user interface system
WE Noori, AS Albahri - Applied Data Science and Analysis, 2023 - mesopotamian.press
Myopia, a prevalent vision disorder with potential complications if untreated, requires early
and accurate detection for effective treatment. However, traditional diagnostic methods often …
and accurate detection for effective treatment. However, traditional diagnostic methods often …