Innovative Data Solutions for Inclusive Cities: The IDEAtlas User Portal by B. Tareke, P. Silva Filho, C. Persello, M. Kuffer, R. V. Maretto, J. Wang, A. Abascal, P. Pillai, B. Singh, J. M. D'Attoli, C. Kabaria, J. Pedrassoli, P. Brito, P. Elias, E. A. Villaseñor, A. Ramírez Santiago, W. Mulyana, J. Pratomo, R. Leska, J. Streitenberger, D. Mwaniki, D. R. Thomson

“…Thus, the IDEAtlas User Portal represents a significant step toward inclusive, evidence-based urban planning and policymaking.…”
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Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning by Jon Alvarez Justo, Alexandru Ghita, Daniel Kovac, Joseph L. Garrett, Mariana-Iuliana Georgescu, Jesus Gonzalez-Llorente, Radu Tudor Ionescu, Tor Arne Johansen

“…Unlike 2D-CNNs and ViTs, which encode both spectral and spatial information, 1D-Justo-LiuNet focuses solely on the rich spectral features in hyperspectral data, benefitting from the high-dimensional feature space. …”
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Application of a Multi‐Layer Artificial Neural Network in a 3‐D Global Electron Density Model Using the Long‐Term Observations of COSMIC, Fengyun‐3C, and Digisonde by Wang Li, Dongsheng Zhao, Changyong He, Yi Shen, Andong Hu, Kefei Zhang

“…However, it is still a challenging mission to develop a model with high predictability that captures the horizontal‐vertical features of ionospheric electrodynamics. In this study, multiple observations during 2005–2019 from space‐borne global navigation satellite system (GNSS) radio occultation (RO) systems (COSMIC and FY‐3C) and the Digisonde Global Ionosphere Radio Observatory are utilized to develop a completely global ionospheric three‐dimensional electron density model based on an artificial neural network, namely ANN‐TDD. …”
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An accurate approach to discriminate android colluded malware from single app malware using permissions intelligence by Roger Yiran Mawoh, Joan Beri Ali Wacka, Franklin Tchakounte, Claude Fachkha, Kolyang

“…The research begins by extracting and identifying key features, such as permissions, smali file size, and permission rates, for model training. …”
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Quantum ensemble learning with a programmable superconducting processor by Jiachen Chen, Yaozu Wu, Zhen Yang, Shibo Xu, Xuan Ye, Daili Li, Ke Wang, Chuanyu Zhang, Feitong Jin, Xuhao Zhu, Yu Gao, Ziqi Tan, Zhengyi Cui, Aosai Zhang, Ning Wang, Yiren Zou, Tingting Li, Fanhao Shen, Jiarun Zhong, Zehang Bao, Zitian Zhu, Zixuan Song, Jinfeng Deng, Hang Dong, Pengfei Zhang, Wei Zhang, Hekang Li, Qiujiang Guo, Zhen Wang, Ying Li, Xiaoting Wang, Chao Song, H. Wang

“…Here, we introduce AdaBoost.Q, a quantum adaptation of the classical adaptive boosting (AdaBoost) algorithm designed to enhance learning capabilities of quantum classifiers. Based on the probabilistic nature of quantum measurement, the algorithm improves the prediction accuracy by refining the attention mechanism during the adaptive training and combination of quantum classifiers. …”
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TRACE Model: Predicting Treatment Response to Transarterial Chemoembolization in Unresectable Hepatocellular Carcinoma by Wang W, Zhang Q, Cui Y, Zhang S, Li B, Xia T, Song Y, Zhou S, Ye F, Xiao W, Cao K, Chi Y, Qu J, Zhou G, Chen Z, Zhang T, Chen X, Ju S, Wang YC

“…Radiomics model was constructed based on the selected features from pretreatment MR images. …”
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A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema by Wenrui Lu, Kunhong Xiao, Xuemei Zhang, Yuqing Wang, Wenbin Chen, Xierong Wang, Yunxi Ye, Yan Lou, Li Li

“…Baseline data included optical coherence tomography (OCT) features and blood-based metabolic and hematologic markers. …”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Despite their prevalence, conventional ratio-based methods often suffer from ambiguity and limited potential for automation applicrations. …”
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OCT5k: A dataset of multi-disease and multi-graded annotations for retinal layers by Mustafa Arikan, James Willoughby, Sevim Ongun, Ferenc Sallo, Andrea Montesel, Hend Ahmed, Ahmed Hagag, Marius Book, Henrik Faatz, Maria Vittoria Cicinelli, Amani A. Fawzi, Dominika Podkowinski, Marketa Cilkova, Diana Morais De Almeida, Moussa Zouache, Ganesham Ramsamy, Watjana Lilaonitkul, Adam M. Dubis

“…This dataset improves upon this with multi-grader and multi-disease labels for training machine learning-based algorithms. The proposed dataset covers three subsets of scans (Age-related Macular Degeneration, Diabetic Macular Edema, and healthy) and annotations for two types of tasks (semantic segmentation and object detection). …”
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The value of a radiomics model in predicting ovarian malignancy: a retrospective multi-center comparison with O-RADS and radiologists by Junjie Jin, Xijia Deng, Ling Long, Meiling Liu, Meimei Cao, Hao Gong, Huan Liu, Xiaosong Lan, Lili Liu, Jiuquan Zhang

“…Radiomics features were extracted from preoperative MRI. Features were selected using minimum redundancy, maximum relevance, and the least absolute shrinkage and selection operator algorithm. …”
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Clinical-radiomics combination model for predicting the short-term efficacy of bipolar transurethral enucleation of the prostate in patients with benign prostatic hyperplasia by Tianyou Zhang, Zijun Mo, Jiayu Huang, Jun Wang, Yiran Tao, Lei Ye, Wenwen Zhong, Bing Yao, Hu Qu, Bo Ma, Dejuan Wang, Jiahui Mo, Chunwei Ye, Junying Zhu, Jianguang Qiu

“…Three prediction models were developed and validated based on clinical-radiological features, radiomic features, and their combinations. …”
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Improvements in aerosol layer height retrievals from TROPOMI oxygen A-band measurements by surface albedo fitting in optimal estimation by M. de Graaf, M. Sneep, M. ter Linden, L. G. Tilstra, D. P. Donovan, G.-J. van Zadelhoff, J. P. Veefkind

“…<p>The aerosol layer height (ALH), from the Sentinel-5P/TROPOMI L2_AER_LH product, is based on an optimal estimation (OE) approach, fitting cloud-free measurements to synthetic reflectances in the strongest oxygen absorption band, provided by a neural network trained with high-resolution simulated reflectances. …”
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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach by Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani

“…Data preprocessing involved noise filtering, feature extraction, and combining handcrafted and automatic features through convolutional and long-short-term memory autoencoders. …”
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Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…Traditional ML models, such as Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extra Trees, Random Forest, and XGBoost, were trained and evaluated. The study further explored the impact of incorporating features derived from autoencoders, particularly focusing on the effect of compression in the bottleneck layer on model performance. …”
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Pengembangan Aplikasi Berlatih Membaca Cepat Berbahasa Inggris Berbasis Progressive Web App dengan Metode Prototyping by Muhammad Fajar Alfath, Lutfi Fanani, Agi Putra Kharisma

“…Based on this observation, a Progressive Web App (PWA) was developed utilizing the SDLC prototyping method. …”
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A Regional Analysis of Diversity, Equity, and Inclusion Initiatives in Plastic Surgery Residency Programs by Dylan G. Choi, BS, Kevin Luu, BS, Gabrielle Brite, BA, Alexander T. Plonkowski, MBBS, MRes, Mariam Al-Hamad Daubs, MD, Aleksandra Krajewski, MD

“…In addition, there was a significant difference in DEI research featured on websites, with the West having the highest rate of features (69.2%, P = 0.019). …”
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NRWI: a novel spectral index optimized for waterbody extraction from high-resolution GF-2 satellite imagery by Peng Zhang, Shanchuan Guo, Hong Fang, Pengfei Tang, Cong Lin, Hui Yang, Biao Wang, Yanlan Wu

“…Remote sensing-based water indices are well-suited for rapid, large-scale waterbody extraction. …”
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Clinical experiences in Turkish paediatric patients with chronic recurrent multifocal osteomyelitis by Betül Sözeri, Nuray Aktay Ayaz, Başak Yıldız Atıkan, Şerife Gül Karadağ, Mustafa Çakan, Mehmet Argın, Murat Sezak

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Predictive modeling of pregnancy outcomes utilizing multiple machine learning techniques for in vitro fertilization-embryo transfer by Ru Bai, Jia-Wei Li, Xia Hong, Xiao-Yue Xuan, Xiao-He Li, Ya Tuo

“…Methods The clinical data and pregnancy outcomes of 2625 women who underwent fresh cycles of IVF-ET between 2016 and 2022 at the Reproductive Center of the Affiliated Hospital of Inner Mongolia Medical University were enrolled to establish a comprehensive dataset. The observed features were preprocessed and analyzed. A predictive model for pregnancy outcomes of IVF-ET treatment was constructed based on the processed data. …”
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Face Mesh for Dementia Detection: Evaluating Data Augmentation in Deep Learning and Traditional Machine Learning by Chuheng Zheng, Mondher Bouazizi, Taichi Okunishi, Tomoaki Ohtsuki, Momoko Kitazawa, Toshiro Horigome, Taishiro Kishimoto

“…Facial features, on the other hand, have been comparatively neglected despite their potential in identifying AD. …”
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