A Deep Learning Approach to Assist in Pottery Reconstruction from Its Sherds by Matheus Ferreira Coelho Pinho, Guilherme Lucio Abelha Mota, Gilson Alexandre Ostwald Pedro da Costa

“…While PointNet was motivated by 3D point cloud classification and segmentation applications, PotNet was designed to perform non-linear regressions. …”
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Explainable AI for Healthcare 5.0: Opportunities and Challenges by Deepti Saraswat, Pronaya Bhattacharya, Ashwin Verma, Vivek Kumar Prasad, Sudeep Tanwar, Gulshan Sharma, Pitshou N. Bokoro, Ravi Sharma

“…Based on the review method and presented research questions, systematically, the article unfolds a proposed architecture that presents an EXAI ensemble on the computerized tomography (CT) image classification and segmentation process. A solution taxonomy of EXAI in Healthcare 5.0 is proposed, and operational challenges are presented. …”
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Machine learning and deep learning in medicine and neuroimaging by Iván Sánchez Fernández, Jurriaan M. Peters

“…We present a narrative review of the relevant literature with a particular focus on deep learning for image classification and image segmentation in neuroimaging. …”
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Radiomics in the differential diagnosis of glioblastoma under the primary neurooncoimaging conditions by Nikita E. Maslov, Daria A. Valenkova, Alexander M. Sinitсa, Gennadiy E. Trufanov, Vladimir M. Moiseenko, Alexander Yu. Efimtsev, Vera V. Chernobrivtseva

“…The most effective combination of tools for preprocessing, segmentation, and classification was found to be ScaleIntensity, LevelTracing, and Random Forest, respectively. …”
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Best practices for AI-based image analysis applications in aquatic sciences: The iMagine case study by Elnaz Azmi, Khadijeh Alibabaei, Valentin Kozlov, Tjerk Krijger, Gabriele Accarino, Sakina-Dorothée Ayata, Amanda Calatrava, Marco Mariano De Carlo, Wout Decrop, Donatello Elia, Sandro Luigi Fiore, Marco Francescangeli, Jean-Olivier Irisson, Rune Lagaisse, Martin Laviale, Antoine Lebeaud, Carolin Leluschko, Enoc Martínez, Germán Moltó, Igor Ruiz Atake, Antonio Augusto Sepp Neves, Damian Smyth, Jesús Soriano-González, Muhammad Arabi Tayyab, Vanessa Tosello, Álvaro López García, Dick Schaap, Gergely Sipos

“…Through these methodologies, iMagine enhances consistency, enabling researchers to efficiently publish and share data in repositories.Beyond its AI tools, iMagine places a strong emphasis on deep learning models, such as convolutional neural networks, for tasks like image classification, object detection, and segmentation, tailored to the unique requirements of aquatic sciences. …”
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A Combined Approach Using T2*-Weighted Dynamic Susceptibility Contrast MRI Perfusion Parameters and Radiomics to Differentiate Between Radionecrosis and Glioma Progression: A Proof... by José Pablo Martínez Barbero, Francisco Javier Pérez García, David López Cornejo, Marta García Cerezo, Paula María Jiménez Gutiérrez, Luis Balderas, Miguel Lastra, Antonio Arauzo-Azofra, José M. Benítez, Antonio Jesús Láinez Ramos-Bossini

“…Key predictive variables included radiomics features like wavelet-HHH_firstorder_Mean and mean normalized TIC values. …”
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Adversarial domain adaptation for deforestation detection in remote sensing imagery by José Matheus Fonseca dos Santos, Pedro Juan Soto Vega, Guilherme Lucio Abelha Mota, Gilson Alexandre Ostwald Pedro da Costa

“…While state-of-the-art deep semantic segmentation networks offer high classification performance, producing the references for supervised training often proves to be quite laborious and costly. …”
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A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights by Muna Alsallal, Hanan Hassan Ahmed, Radhwan Abdul Kareem, Anupam Yadav, Subbulakshmi Ganesan, Aman Shankhyan, Sofia Gupta, Kamal Kant Joshi, Hayder Naji Sameer, Ahmed Yaseen, Zainab H. Athab, Mohaned Adil, Bagher Farhood

“…The study used two deep learning models—DenseNet121 and EfficientNet-B0—enhanced with attention mechanisms to improve accuracy. A combined classification approach used both radiomic and deep learning features, and machine learning models like Random Forest, XGBoost, and CatBoost were applied. …”
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Application of artificial intelligence-based computer vision methods in liver diseases: a bibliometric analysis by Yutian Feng, Qi Wang, Yuxin Su, Wenrui Ma, Guifang Du, Jian Wu, Juan Liu, Yunfang Wang

“…Techniques such as image segmentation, classification, and registration are prevalent, meeting clinical needs like lesion detection and disease prognosis. …”
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Adaptive capacity management in municipalities in the Semiarid region of Brazil: Application of a composite index by Yonara Claudia dos Santos, Zoraide Souza Pessoa

“…The method used is based on data from the Municipal Basic Information Survey (Munic/IBGE) and operates on a scale from 0 to 1, segmented into five strata corresponding to classification levels ranging from classification levels ranging from “very low” to “very high”. …”
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Characterizing Breast Tumor Heterogeneity Through IVIM-DWI Parameters and Signal Decay Analysis by Si-Wa Chan, Chun-An Lin, Yen-Chieh Ouyang, Guan-Yuan Chen, Chein-I Chang, Chin-Yao Lin, Chih-Chiang Hung, Chih-Yean Lum, Kuo-Chung Wang, Ming-Cheng Liu

“…Evaluation using 3D-ROC analysis also indicated that the DNN was the best detector based on metrics like target detection rate and overall effectiveness. …”
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Unveiling Multistability in Urban Traffic Through Percolation Theory and Network Analysis by Rui Chen, Jiazhen Liu, Yong Li, Yuming Lin

“…Leveraging data-driven clustering and classification techniques, we demonstrated that road segments with high betweenness centrality are disproportionately likely to become congested, and that the top 1% most topologically important roads accurately predict both stable state types and the joint behavior of <i>G</i> and <i>f</i>. …”
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Multivariate Examination of Metabolic Contributions to Beef Longissimus Lumborum Flavor by Adria Grayson, D. Andy King, Jeffrey Savell, Kerri Gehring, Rhonda K Miller, Russell McKeith, Steven D Shackelford, Tommy L. Wheeler

“…These data indicate that clustering was effective in segmenting them into groupings more indicative of the metabolic machinery than pH alone. …”
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Metagenome analysis of viruses associated with Anopheles mosquitoes from Ramu Upazila, Cox’s Bazar District, Bangladesh by Tao Li, Mohammad Shafiul Alam, Yu Yang, Hasan Mohammad Al-Amin, Mezanur Rahman, Farzana Islam, Matthew A. Conte, Dana C. Price, Jun Hang

“…Homology-based taxonomic classification and phylogenetic analyses identified a broad diversity of putative viruses from 12 known families, with additional unclassified viruses also likely present. …”
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Network screening and analysis of pedestrian and bicyclist crashes on Florida arterials using a corridor-level approach by John McCombs, Haitham Al-Deek, Adrian Sandt

“…This approach uses less data than site-level analyses while also considering the relationship between intersections and roadway segments. 548 roadway corridors covering over 1000 centerline miles (1609 km) were identified on urban and suburban arterial roads in seven Florida counties based on context classification and lane count. …”
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Central Serous Chorioretinopathy from the Point of View of OCT-Angiography. Part 1. Chorioretinal Blood Flow Changes by A. G. Shchuko, S. I. Zhukova, T. N. Iureva, A. N. Zlobina

“…Thus, the introduction into clinical practice of optical coherence tomography in the angiography (OCTA) mode made it possible to visualize the retinal and choroidal vessels taking into account their segmentation, which opens up prospects for studying chorioretinal blood flow in the CSR. …”
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Hierarchical long short term memory recurrent neural network for goats behaviour prediction from accelerometer data by Mathieu Bonneau, Laura Faillot, Willy Troupe, Lucile Riaboff

“…A hierarchical LSTM model was then built to derive behaviours from a given accelerometer signal, by sequentially combining several models that first tackle simple classification tasks (e.g., grazing or non-grazing segments), then increasingly complex ones (e.g., displacement or other activities), progressively withdrawing segments that have already been identified. …”
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Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer’s disease progression by Sepehr Aghajanian, Fateme Mohammadifard, Ida Mohammadi, Shahryar Rajai Firouzabadi, Ali Baradaran Bagheri, Elham Moases Ghaffary, Omid Mirmosayyeb

“…MRI volumes underwent bias correction, segmentation, and radiomics feature extraction. A 3D residual network (ResNet3D) was trained using a pairwise ranking loss to capture single-timepoint risk scores. …”
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Renewable Energy Index: The Country-Group Performance Using Data Envelopment Analysis by Geovanna Bernardino Bello, Luana Beatriz Martins Valero Viana, Gregory Matheus Pereira de Moraes, Diogo Ferraz

“…The REI incorporates new factors such as agricultural methane emissions (thousand metric tons of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>CO</mi><mn>2</mn></msub></semantics></math></inline-formula> equivalent), PM2.5 air pollution exposure (µg/m³), and aspects related to electricity, including consumption (as % of total final energy consumption), production from renewable sources, excluding hydroelectric (kWh), and accessibility in rural and urban areas (% of population with access), aligning with the emerging paradigm outlined by the United Nations. By segmenting the REI into global, developmental, and income group classifications, this study conducts the Mann–Whitney U test and the Kruskal–Wallis H tests to identify variations in renewable energy efficiency among different country groups. …”
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Analyzing the Impact of the Presence of Foreign Tourists in Religious Places on Their Attitude Towards Shiism by Marziyeh Farshiddost, Behrooz Badkoo, Mohamad Ghasemisiani

“…There are religious, retreats, guesthouses, adventures, extended family visits, volunteer activities, generational and intergenerational transitions. Different segments of religious tourism as described by Stausberg (2011) include pilgrimages, conferences, seminars, spiritual retreats and festivals. …”
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