Architecture-Aware Augmentation: A Hybrid Deep Learning and Machine Learning Approach for Enhanced Parkinson’s Disease Detection by Madjda Khedimi, Tao Zhang, Hanine Merzougui, Xin Zhao, Yanzhang Geng, Khamsa Djaroudib, Pascal Lorenz

“…This study examines the performance of hybrid deep learning and machine learning models in detecting PD using spiral drawings, with a focus on the impact of data augmentation techniques. We compare the accuracy of Vision Transformer (ViT) with K-Nearest Neighbors (KNN), Convolutional Neural Networks (CNN) with Support Vector Machines (SVM), and Residual Neural Networks (ResNet-50) with Logistic Regression, evaluating their performance on both augmented and non-augmented data. …”
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A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…Because learning from such large datasets is difficult, medical imaging data analysis is becoming increasingly popular employing bio-inspired enabled deep learning models. …”
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Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care by Rahul Kumar, Kyle Sporn, Akshay Khanna, Phani Paladugu, Chirag Gowda, Alex Ngo, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

“…We examine integrating quantitative imaging features from MRI, CT, and PET with genomic and transcriptomic data to enable non-invasive tumor profiling. …”
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Open-Source High-Throughput Phenotyping for Blueberry Yield and Maturity Prediction Across Environments: Neural Network Model and Labeled Dataset for Breeders by Jing Zhang, Jerome Maleski, Hudson Ashrafi, Jessica A. Spencer, Ye Chu

“…We aim to facilitate further research in computer vision and precision agriculture by publishing the labeled image dataset and the trained model. In this research, true-color images of blueberry bushes were collected, annotated, and used to train a deep neural network object detection model [You Only Look Once (YOLOv11)] to detect mature and immature berries. …”
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Reduced microstructural white matter integrity is associated with the severity of physical symptoms in functional neurological disorder by Nicolas Gninenko, Eliane Müller, Selma Aybek

“…Methods: Diffusion-weighted imaging data were collected from 85 FND patients with mixed symptoms and 75 healthy controls (HCs), together with illness duration, clinician-rated (S-FMDRS & CGI), and patient-reported (SF-36) symptom severity. …”
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Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

“…This paper follows two methodologies and their simulation outcomes are compared for performance evaluation. In the first part, data augmentation is performed on the PlantVillage data set images (for apple, corn, potato, tomato, and rice plants), and their deep features are extracted using convolutional neural network (CNN). …”
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Mapping the anterolateral ligament of the knee: a bibliometric analysis by Hale Öktem, Yusuf Jamil, Sinem Nur Sever

“…VOSviewer software was used to analyze co-authorship network analysis, keyword co-occurrence mapping, and total citation analysis. …”
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Altered fronto-parietal alpha synchronization and coherence in paranormal believers by Abdolvahed Narmashiri, Kiomars Sharifi, Reza Khosrowabadi, Javad Hatami

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Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function by Imran Uddin, Dzati A. Ramli, Abdullah Khan, Javed Iqbal Bangash, Nosheen Fayyaz, Asfandyar Khan, Mahwish Kundi

“…In the area of machine learning, different techniques are used to train machines and perform different tasks like computer vision, data analysis, natural language processing, and speech recognition. …”
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Multimodal Sentiment Analysis Based on Expert Mixing of Subtask Representations by Ling Lei, Wangjun He, Qiuyan Zheng, Bing Zhu

“…To maximize the utilization of non-linguistic modality information in multimodal data, this paper proposes a subtask representation selection module based on an expert mixture to enhance the feature representation capabilities of speech and image subtasks. …”
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Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (Neuro-Fuzzy Network) Method in Forest Degradation (Case Study: Sari County) by somayeh mehrabadi

“…In this study, forest degradation was modeled by employing the single-perceptron neural network and hybrid neuro-fuzzy method. For this purpose, the images from Landsat-5 TM sensor in 1999 and Landsat 8 OLI sensor in 2017 were utilized. …”
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An Open Platform for RGB Composite Analysis and Validation: RGB_DIGI by A. N. Arslan, A. N. Arslan, C. M. Tanis

“…In this paper we present an open platform which consists of a free automated digital image processing tool, a camera network portal where digital images are available freely, operational monitoring system and Cal / Val activities producing near real time results for comparison of satellite-derived products with webcam derived and in-situ data. …”
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A bibliometric analysis of studies on artificial intelligence in neuroscience by Ugur Tekin, Murat Dener, Murat Dener

“…Artificial intelligence (AI) techniques, particularly deep learning and machine learning, offer transformative solutions by improving the analysis of complex neural data, facilitating early diagnosis, and enabling personalized treatment approaches. …”
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Downscaling and Gap-Filling GRACE-Based Terrestrial Water Storage Anomalies in the Qinghai–Tibet Plateau Using Deep Learning and Multi-Source Data by Jun Chen, Linsong Wang, Chao Chen, Zhenran Peng

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Analysis and correcting pronunciation disorders based on artificial intelligence approach by Nataliia Melnykova, Bohdan Pavlyk, Oleh Basystiuk, Stepan Skopivskyi

“…The analysis of machine learning methods led to the selection of two experimental models: a Convolutional Neural Network (CNN) utilizing mel-spectrograms for image-based sound representation and a Long Short-Term Memory (LSTM) network combined with mel-frequency cepstral coefficients, aiming to explore the effectiveness of sequential data processing in the context of pronunciation disorder classification in post-traumatic military patients. …”
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Transfer learning‑based attenuation correction in 99mTc-TRODAT-1 SPECT for Parkinson’s disease using realistic simulation and clinical data by Wenbo Huang, Han Jiang, Yu Du, Haiyan Wang, Hao Sun, Guang-Uei Hung, Greta S. P. Mok

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Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow by Shan Sun, Fei Wang, Fen Xu, Yufeng Deng, Jiwang Ma, Kai Chen, Sheng Guo, X. San Liang, Tao Zhang

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Temperature prediction for forging a large S355NL steel flange for offshore wind turbines using neural network and numerical simulation by Yu Chen, Jinfu Zhao, Ling Kong, Jianjun Zhang, Zhixin Huang, Dayong Li, Yuhui Wang

“…By applying back propagation (BP) neural network algorithms to finite element simulation data, the study achieved precise modeling of temperature trends in the forging process, with a maximum error below 1 %, enabling online temperature predictions. …”
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Advanced Cotton Boll Segmentation, Detection, and Counting Using Multi-Level Thresholding Optimized with an Anchor-Free Compact Central Attention Network Model by Arathi Bairi, Uma N. Dulhare

“…A proposed technique was developed to overcome these issues and enhance the performance of the detection and counting of cotton bolls. Initially, data were gathered from the dataset, and a pre-processing stage was performed to enhance image quality. …”
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High-frequency stock price prediction via deep learning by Jianlong Bao, Takayuki Morimoto

“…In addition, the same dataset (one-dimensional time series without image conversion) is used to train Artificial Neural Network(ANN), Long Short-Term Memory(LSTM), and one-dimensional convolutional neural network(1D-CNN) models, enabling a performance comparison with the results of the image-based prediction method.…”
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