Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

“…These computational techniques have become essential for addressing the inherent complexity and high-dimensionality of microbiome data, which consist of different types of omics datasets. Deep learning algorithms have shown remarkable capabilities in pattern recognition, feature extraction, and predictive modeling, enabling researchers to uncover hidden relationships within microbial ecosystems. …”
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Elderly travel mode choice in Thailand-evaluating MNL and machine learning models by Anantaya Philuek, Panuwat Wisutwattanasak, Fareeda Watcharamaisakul, Chinnakrit Banyong, Anon Chantaratang, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

“…This investigation analyzes the determinants of transportation mode selection among elderly populations in Thailand through a comparative approach utilizing both traditional statistical modeling and contemporary machine learning techniques. The research compares the predictive effectiveness of the Multinomial Logistics Regression (MNL) model against advanced algorithmic approaches including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost) in forecasting elderly travel behavior. …”
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Multi-Temporal Remote Sensing Satellite Data Analysis for the 2023 Devastating Flood in Derna, Northern Libya by Roman Shults, Ashraf Farahat, Muhammad Usman, Md Masudur Rahman

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Detection and monitoring of Melampsora spp. Damage in multiclonal poplar plantations coupling biophysical models and Sentinel-2 time series by Carlos Camino, Alexey Valero-Jorge, Erika García Lima, Ramón Álvarez, Pieter S.A. Beck, Flor Álvarez-Taboada

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Measuring and modeling waterlogging tolerance to predict the future for threatened lowland ash forests by E. J. Gustafson, D. R. Bronson, M. A. Windmuller-Campione, R. A. Slesak, D. M. Donner

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POLARIZATION REPRODUCTION OF STRUCTURAL ANISOTROPY MAPS OF BRAIN PREPARATIONS FOR DIFFERENTIAL DIAGNOSTICS OF HEMORRHAGES OF TRAUMATIC AND NON-TRAUMATIC GENESIS by М. Гараздюк, О. Ушенко, О. Дуболазов

“…The purpose and tasks of the research. To experimentally test and determine a set of markers for differential diagnosis of the cause of death due to the formation of hemorrhages of traumatic and non-traumatic genesis in the substance of the human brain by using the Muller matrix mapping method with algorithmic reproduction of linear birefringence of native histological brain sections. …”
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Automatic identification of Dong Son antique glass artifacts using evolving learning by Anh-Khoi Ngo-Ho, Hoang-Bac Bui, Van-Trieu Pham

“…This approach, which has gained prominence in the field of archaeology worldwide over the past five years, aims to integrate advanced technology into Vietnamese archaeology. Our research is motivated by the unique conditions present in archaeology, where we seek to employ evolving learning algorithms to archaeological databases, comparing and selecting the most suitable model that aligns with the archeological dataset's performance. …”
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AI‐Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis by Caglar Ozturk, Daniel H. Pak, Luca Rosalia, Debkalpa Goswami, Mary E. Robakowski, Raymond McKay, Christopher T. Nguyen, James S. Duncan, Ellen T. Roche

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A rapid, affordable, and reliable method for profiling microbiome biomarkers from fecal images by Donghyeok Lee, Annemiek Maaskant, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A.M. Langermans, Evgeni Levin

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The urban heat Island effect: A review on predictive approaches using artificial intelligence models by Ali Najah Ahmed, Nouar AlDahoul, Nurhanani A. Aziz, Y.F. Huang, Mohsen Sherif, Ahmed El-Shafie

“…While conventional ML algorithms remain widely used, DL and hybrid models have shown superior performance in predictive accuracy. …”
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Thermographic Data Processing and Feature Extraction Approaches for Machine Learning-Based Defect Detection by Alexey Moskovchenko, Michal Svantner

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Algorhythmic governance: Regulating the ‘heartbeat’ of a city using the Internet of Things by Claudio Coletta, Rob Kitchin

“…Drawing on Lefebvre, and subsequent research, we employ rhythmanalysis in conjunction with Miyazaki’s notion of ‘algorhythm’ and nascent work on algorithmic governance, to develop a concept of ‘algorhythmic governance’. …”
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Comparative analysis of machine learning techniques in metabolomic-based preterm birth prediction by Ying-Chieh Han, Jane Shearer, Chunlong Mu, Donna M. Slater, Suzanne C. Tough, Gavin E. Duggan

“…Background: Machine learning (ML), with advancements in algorithms and computations, is seeing an increased presence in life science research. …”
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ALLERGY TO ANTIBIOTICS IN CHILDREN: WHO IS TO BLAME AND WHAT TO DO? by I. V. Andreeva, O. U. Stetsyuk

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Optimisation tools for meeting nutrient requirements of Indian children and adults at optimal cost by Fathima Ayoob, Jawahar R. Manivannan, Ashikh Ahmed, Afsal K. Murikkanchery, Abhishek Kumar, Santu Ghosh, Patrick Webb, Anura V. Kurpad, Tinku Thomas

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What are new opportunities for clinical practice the VERIFY study opens and which values for native diabetes patients? Joint conclusion on the advisory board results. November 6, 2... by Marina V. Shestakova, Mikhail B. Antsiferov, Alexander S. Ametov, Gagik R. Galstyan, Tatiana Y. Demidova, Alexey V. Zilov, Tatiana N. Markova, Nina A. Petunina, Natalya A. Chernikova, Minara S. Shamkhalova

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An improved deep CNN-based freshwater fish classification with cascaded bio-inspired networks by Asadullah Shaikh, Wahidur Rahman, Kaniz Roksana, Tarequl Islam, Mohammad Motiur Rahman, Hani Alshahrani, Adel Sulaiman, Mana Saleh Al Reshan

“…Traditional methods are very insufficient to overcome these issues. To address these research gaps, the research proposes an automatic system for categorizing Bangladesh's freshwater fish. …”
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Multi-source 3D point clouds fusion for potential rock mass hazard evaluation in high-steep rock slopes by W. Yuan, C. Liu, C. Liu, T. Wang, B. Adriano, H. Bao, R. Shibasaki, S. Koshimura

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Study of Synergetic Optimization Operation for Distribution Network Considering Multiple Reactive Power Output Modes of Photovoltaics and Different Port Numbers of Flexible Interco... by Yijin Li, Jibo Wang, Zihao Zhang, Wenhao Xu, Ming Wu, Geng Niu

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Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk by Mohammad Amin Hemmati, Marzieh Monemi, Shima Asli, Sina Mohammadi, Behina Foroozanmehr, Dariush Haghmorad, Valentyn Oksenych, Majid Eslami

“…Early detection is made easier by machine learning algorithms that improve the categorization of cancer kinds based on microbiological data. …”
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