Innovative Approach to Detecting Autism Spectrum Disorder Using Explainable Features and Smart Web Application by Mohammad Abu Tareq Rony, Fatama Tuz Johora, Nisrean Thalji, Ali Raza, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

“…We used a standard dataset comprising 1054 patient samples and 20 variables. The research methodology involved rigorous preprocessing, including selecting key variables through data mining (DM) visualization techniques including Chi-Square tests, analysis of variance, and correlation analysis, along with outlier removal to ensure robust model performance. …”
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Precision enhancement in wireless capsule endoscopy: a novel transformer-based approach for real-time video object detection by Tsedeke Temesgen Habe, Keijo Haataja, Pekka Toivanen

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Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

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Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data by Md Ariful Islam Mozumder, Tagne Poupi Theodore Armand, Rashadul Islam Sumon, Shah Muhammad Imtiyaj Uddin, Hee-Cheol Kim

“…The approach achieved a satisfactory accuracy of 98.9% while detecting the activity useful for cat well-being.…”
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Application of AI in Date Fruit Detection—Performance Analysis of YOLO and Faster R-CNN Models by Seweryn Lipiński, Szymon Sadkowski, Paweł Chwietczuk

“…., YOLOv8n and Faster R-CNN, for automated detection of date fruits in natural orchard environments. …”
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Multimodal AI-driven object detection with uncertainty quantification for cardiovascular risk assessment in autistic patients by Ling Tang, Chengchao Shen

“…IntroductionArtificial Intelligence (AI) has transformed medical diagnostics, offering enhanced precision and efficiency in detecting cardiovascular risks. …”
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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

“…However, due to the variability in scale and shape of PV installations in complex environments, the detection results often fail to capture detailed information and struggle to scale for multi-scale PV systems. …”
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Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial by Dung-Jang Tsai, Chin Lin, Wei-Ting Liu, Chiao-Chin Lee, Chiao-Hsiang Chang, Wen-Yu Lin, Yu-Lan Liu, Da-Wei Chang, Ping-Hsuan Hsieh, Chien-Sung Tsai, Yuan-Hao Chen, Yi-Jen Hung, Chin-Sheng Lin

“…Secondary outcomes included echocardiogram utilization rates, positive predictive value for low EF detection, and cardiology consultation rates. Statistical analysis included hazard ratios (HR) with 95% confidence intervals (CI) for time-to-event outcomes and chi-square tests for categorical variables. …”
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Unraveling deep-learning detection of atmospheric Kármán vortex streets: dataset, baseline benchmarking, and optimization by Yihan Zhang, Chaoyue Wu, Qiao Su, Yuqi Zhang, Daoyi Chen

“…However, their automated detection and the influence of atmospheric variables on their formation remain insufficiently explored. …”
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Analyzing the Efficacy of Artificial Intelligence in Facilitating Medico-Legal Investigations and Enhancing Forensic Processes for Emergency Trauma Patients: A Systematic Review by Rajiv Ratan Singh, Sachin Kumar Tripathi, Azad Kumar Bharti, Pradeep Kumar Yadav

“…Since the technology’s introduction, many people have been interested in using artificial intelligence (AI) to enhance trauma and emergency care procedures. …”
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Detection of COPD exacerbations with continuous monitoring of breathing rate and inspiratory amplitude under oxygen therapy by Juliana Alves Pegoraro, Antoine Guerder, Thomas Similowski, Philippe Salamitou, Jesus Gonzalez-Bermejo, Etienne Birmelé

“…In this study, we look to improve the previously described method, by combining breathing variables, using multiple daily measures, and using an artificial intelligence-based novelty detection approach. …”
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Association between parental education level and intelligence quotient of children referred to the mental healthcare system: a cross-sectional study in Poland by Urszula Sajewicz-Radtke, Ariadna Łada-Maśko, Michał Olech, Paweł Jurek, Łucja Bieleninik, Bartosz M. Radtke

“…Linear regression analysis was performed using staircase coding for ordinal predictors with several binary independent variables. A significant correlation was found between parental education levels and IQ of the sampled children, with higher levels of parents’ education predicting higher IQ scores, particularly with mother’s education explaining 18.23% of the variance in children’s overall intelligence. …”
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data by T. Radke, S. Fuchs, C. Wilms, I. Polkova, I. Polkova, I. Polkova, M. Rautenhaus, M. Rautenhaus

“…We also demonstrate application of the approach for finding the most relevant input variables (TMQ is found to be most relevant, while surface pressure is rather irrelevant) and evaluating detection robustness when changing the input domain (a CNN trained on global data can also be used for a regional domain, but only partially contained features will likely not be detected). …”
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Artificial Intelligence-based Blockchain Technology for Skin Cancer Investigation Complemented with Dietary Assessment and Recommendation using Correlation Analysis in Elder Indivi... by Suman Mann, Archana Balyan, Vinita Rohilla, Deepa Gupta, Zatin Gupta, Abdul Wahab Rahmani

“…The detection of melanomas supports the patient in enhancing the prognosis and support in discriminating between the melanomas and less impact lesions. …”
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Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging by Oliver Lester Saldanha, Jiefu Zhu, Gustav Müller-Franzes, Zunamys I. Carrero, Nicholas R. Payne, Lorena Escudero Sánchez, Paul Christophe Varoutas, Sreenath Kyathanahally, Narmin Ghaffari Laleh, Kevin Pfeiffer, Marta Ligero, Jakob Behner, Kamarul A. Abdullah, Georgios Apostolakos, Chrysafoula Kolofousi, Antri Kleanthous, Michail Kalogeropoulos, Cristina Rossi, Sylwia Nowakowska, Alexandra Athanasiou, Raquel Perez-Lopez, Ritse Mann, Wouter Veldhuis, Julia Camps, Volkmar Schulz, Markus Wenzel, Sergey Morozov, Alexander Ciritsis, Christiane Kuhl, Fiona J. Gilbert, Daniel Truhn, Jakob Nikolas Kather

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Effect of Droplet Contamination on Camera Lens Surfaces: Degradation of Image Quality and Object Detection Performance by Hyunwoo Kim, Yoseph Yang, Youngkwang Kim, Dong-Won Jang, Dongil Choi, Kang Park, Sangkug Chung, Daegeun Kim

“…This paper quantitatively evaluates the effect of droplet contamination on image quality and object detection performance. Image quality degradation was analyzed using the modulation transfer function (MTF), with droplet volume and number as variables. …”
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DMAC: Discovering Multi-Attribute Correlations of Deep Quality Features for Defect Detection in Mechanical Components by Yue Yu

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A Lightweight Model for Shine Muscat Grape Detection in Complex Environments Based on the YOLOv8 Architecture by Changlei Tian, Zhanchong Liu, Haosen Chen, Fanglong Dong, Xiaoxiang Liu, Cong Lin

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RSDCNet: An efficient and lightweight deep learning model for benign and malignant pathology detection in breast cancer by Yuan Liu, Haipeng Li, Zhu Zhu, Chen Chen, Xiaojing Zhang, Gongsheng Jin, Hongtao Li

“…Consequently, the development of an efficient, automated, and precise pathological detection method is crucial. Methods This study introduces RSDCNet, an enhanced lightweight neural network architecture designed for the automatic detection of benign and malignant breast cancer pathology. …”
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One-class support vector machines for detecting population drift in deployed machine learning medical diagnostics by William S. Jones, Daniel J. Farrow

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