Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review by Andrea Vescio, Gianluca Testa, Marco Sapienza, Filippo Familiari, Michele Mercurio, Giorgio Gasparini, Sergio de Salvatore, Fabrizio Donati, Federico Canavese, Vito Pavone

“…Bone age estimation using DL models often matched or outperformed traditional methods. However, most studies lacked external validation, and many relied on small or single-institution datasets. …”
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Leveraging Machine Learning and Remote Sensing for Water Quality Analysis in Lake Ranco, Southern Chile by Lien Rodríguez-López, Lisandra Bravo Alvarez, Iongel Duran-Llacer, David E. Ruíz-Guirola, Samuel Montejo-Sánchez, Rebeca Martínez-Retureta, Ernesto López-Morales, Luc Bourrel, Frédéric Frappart, Roberto Urrutia

“…Among these models, LSTM stands out as the most effective, with the best metrics in the estimation, the best performance was Case 1, with R² = 0.89, an RSME of 0.32 µg/L, an MAE 1.25 µg/L and an MSE 0.25 (µg/L)², consistently outperforming the others according to the static metrics used for validation. …”
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Multimodal diagnosis of Alzheimer’s disease based on resting-state electroencephalography and structural magnetic resonance imaging by Junxiu Liu, Junxiu Liu, Shangxiao Wu, Shangxiao Wu, Shangxiao Wu, Qiang Fu, Qiang Fu, Xiwen Luo, Xiwen Luo, Yuling Luo, Yuling Luo, Sheng Qin, Sheng Qin, Yiting Huang, Yiting Huang, Zhaohui Chen, Zhaohui Chen

“…However, the inclusion of electroencephalography (EEG) in such multimodal studies has been relatively limited. Moreover, most multimodal studies on AD use convolutional neural networks (CNNs) to extract features from different modalities and perform fusion classification. …”
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Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…Among the studies included in the final synthesis, Convolutional Neural Networks (CNN) emerged as the most frequently applied category of ML models, present in 17 studies (32%). …”
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Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome by Frederik M Zimmermann, Pim A L Tonino, Arjan Koks, Jesse P A Demandt, Marcel van ’t Veer, Pieter-Jan Vlaar, Thomas P Mast, Konrad A J van Beek, Marieke C V Bastiaansen

“…Objectives Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). …”
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GAN-enhanced deep learning for improved Alzheimer's disease classification and longitudinal brain change analysis by Purushottam Pandey, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Jyoti Pruthi, Eid Albalawi, Ali Algarni, Ahlam Almusharraf

“…The ResNet101 model is augmented with innovative layers such as the pattern descriptor parsing operation (PDPO) and the detection convolutional kernel layer (DCK), which are designed to extract the most relevant features from datasets such as ADNI and OASIS. …”
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Deep Learning and Image Generator Health Tabular Data (IGHT) for Predicting Overall Survival in Patients With Colorectal Cancer: Retrospective Study by Seo Hyun Oh, Youngho Lee, Jeong-Heum Baek, Woongsang Sunwoo

“…To interpret model decisions, gradient-weighted class activation mapping (Grad-CAM) was applied to visualize regions of the input images that contributed most to predictions, enabling identification of key prognostic features. …”
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The Management of Cardiometabolic Risk in MAFLD: Therapeutic Strategies to Modulate Deranged Metabolism and Cholesterol Levels by Annalisa Pezzoli, Ludovico Abenavoli, Marialaura Scarcella, Carlo Rasetti, Gianluca Svegliati Baroni, Jan Tack, Emidio Scarpellini

“…Among these, Pro-protein Convertase Subtilisin/Kexin type 9 inhibitors (PCSK9i) show the most promising efficacy profile but data on liver fibrosis are lacking. …”
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Research on Atlantic surface pCO2 reconstruction based on machine learning by Jiaming Liu, Jie Wang, Xun Wang, Yixuan Zhou, Runbin Hu, Haiyang Zhang

“…Notably, the Copernicus pCO2 and CODC-GOSD pCO2 contribute the most, with both contributing ∼0.72. These are followed by TP, latitude, longitude, SHWW, U10, and E. (2) After comprehensive data testing, the six machine learning models select the optimal hyperparameters for reconstruction. …”
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STYLISTIC MEANS OF IMPLEMENTING THE IDEA OF THE WORLD’S IRIDESCENCE IN PH.K. DICK’S “UBIK” IN THE CONTEXT OF TRANSLATION TRANSFORMATIONS by Svitlana F. Aleksenko, Larysa I. Taranenko

“…Grammatical transformations com- pose nearly two fifths (39.8 %) of the researched body of units, the most efficient ones being substitution and word order change. …”
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Irrigated rice-field mapping in Brazil using phenological stage information and optical and microwave remote sensing by Andre Dalla Bernardina Garcia, MD Samiul Islam, Victor Hugo Rohden Prudente, Ieda Del’Arco Sanches, Irene Cheng

“…Analytic results show that the end of season is the most suitable for obtaining a reliable classification based on optical and SAR sensors. …”
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Anomaly Detection Algorithms for Real-Time Log Data Analysis at Scale by Andras Horvath, Andras Olah, Attila Pinter, Balint Siklosi, Gergely Lukacs, Istvan Z. Reguly, Kalman Tornai, Tamas Zsedrovits, Zoltan Mathe

“…Our results underscore the importance of selecting the right balance between sophistication and simplicity, challenging the assumption that the most sophisticated methods are necessary for effective anomaly detection in real-world log data.…”
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Artificial Intelligence for Detecting COVID-19 With the Aid of Human Cough, Breathing and Speech Signals: Scoping Review by Mouzzam Husain, Andrew Simpkin, Claire Gibbons, Tanya Talkar, Daniel Low, Paolo Bonato, Satrajit S. Ghosh, Thomas Quatieri, Derek T. O'Keeffe

“…Half of the publications and Apps were from the USA. The most prominent AI architecture used was a convolutional neural network, followed by a recurrent neural network. …”
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One Health interventions and challenges under rural African smallholder farmer settings: A scoping review by Evanson R. Omuse, Honest Machekano, Bonoukpoè M. Sokame, Daniel M. Mutyambai, Thomas Dubois, Sevgan Subramanian, Frank Chidawanyika

“…This has led to more convoluted health challenges, for which African smallholder farmers bear the brunt. …”
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Intelligent decision-making and regulation method of gas extraction “borehole-pipe network” system by Kai WANG, Dongxu WANG, Aitao ZHOU, Junwen ZHANG, Fangzhou SONG, Chang’ang DU, Yushuang HAO, Xihui FAN, Wei ZHAO

“…Therefore, in order to regulate the negative pressure of gas extraction system reasonably and accurately, four prediction algorithms are compared and analyzed, and the most excellent prediction algorithm is selected and improved according to its own shortcomings. …”
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NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning by Jianliang Wang, Chen Chen, Jiacheng Wang, Zhaosheng Yao, Ying Wang, Yuanyuan Zhao, Yi Sun, Fei Wu, Dongwei Han, Guanshuo Yang, Xinyu Liu, Chengming Sun, Tao Liu

“…Notably, the accuracy improvement in later growth periods was most pronounced for cotton and maize, with average R² increases of 0.15 and 0.14, respectively, whereas wheat exhibited a more modest improvement of only 0.04. …”
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Enhancing head and neck cancer detection accuracy in digitized whole-slide histology with the HNSC-classifier: a deep learning approach by Haiyang Yu, Haiyang Yu, Wang Yu, Wang Yu, Yuan Enwu, Yuan Enwu, Yuan Enwu, Jun Ma, Jun Ma, Xin Zhao, Xin Zhao, Linlin Zhang, Linlin Zhang, Linlin Zhang, Fang Yang, Fang Yang, Fang Yang

“…Head and neck squamous cell carcinoma (HNSCC) represents the sixth most common cancer worldwide, with pathologists routinely analyzing histological slides to diagnose cancer by evaluating cellular heterogeneity, a process that remains time-consuming and labor-intensive. …”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…Knowledge distillation stands out as it transfers knowledge from large teacher models to compact student models without modifying the network structure, enabling the student models to perform nearly as well as their larger counterparts. However, most distillation techniques have been optimized for image classification, not object detection, which involves simultaneously detecting and classifying multiple target objects within natural images. …”
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Synthesizing field plot and airborne remote sensing data to enhance national forest inventory mapping in the boreal forest of Interior Alaska by Pratima Khatri-Chhetri, Hans-Erik Andersen, Bruce Cook, Sean M. Hendryx, Liz van Wagtendonk, Van R. Kane

“…Among the various topographic factors, we found that elevation was the most important factor for discriminating all forest types. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…Seasonal wind speed analysis revealed distinct patterns, with winter emerging as the most efficient season for wind, featuring a median wind speed of 7.96 m/s. …”
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