UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases by Marco Capó, Silvia Vitali, Georgios Athanasiou, Nicole Cusimano, Daniel García, Garth Cruickshank, Bipin Patel

“…In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. …”
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MetaTrans-FSTSF: A Transformer-Based Meta-Learning Framework for Few-Shot Time Series Forecasting in Flood Prediction by Jiange Jiang, Chen Chen, Anna Lackinger, Huimin Li, Wan Li, Qingqi Pei, Schahram Dustdar

“…The scarcity of historical data can severely hinder the generalization capabilities of traditional deep learning models, presenting a notable challenge in practical flood prediction applications. …”
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Detection of Aspergilloma Disease Using Feature-Selection-Based Vision Transformers by Siyami Aydın, Mehmet Ağar, Muharrem Çakmak, Mustafa Koç, Mesut Toğaçar

“…Recent advancements in next-generation technologies have made them crucial for disease detection. Deep-learning models, which benefit from continuous technological advancements, are already integrated into current early diagnosis systems. …”
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Pendeteksi Citra Masker Wajah Menggunakan CNN dan Transfer Learning by Mohammad Farid Naufal, Selvia Ferdiana Kusuma

“…Convolutional Neural Network (CNN) merupakan algoritma deep learning yang memiliki performa bagus dalam klasifikasi citra. …”
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Field Development Optimization for Low-Productivity Gas Wells under Intermittent Production by Wei Tian, Yi Liu, Xuri Li, Youliang Jia, Yixuan Wang, Li Li, Zhengyan Zhao, Weihong Ding, Wenxin Zhou, Wenyue Sun

“…Therefore, an optimization method for intermittent gas wells based on particle swarm optimization (PSO) algorithm and deep-learning model is proposed. The PSO algorithm determines the optimal schedule, while the deep-learning model forecasts key cycle parameters for these potential schedules. …”
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Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis by Termeh Sarrafan Sadeghi, Seyed AmirHossein Ourang, Fatemeh Sohrabniya, Soroush Sadr, Parnian Shobeiri, Saeed Reza Motamedian

“…Abstract Background Artificial intelligence (AI) methods, including machine learning and deep learning, are increasingly applied in orthodontics for tasks like assessing skeletal maturity. …”
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Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions by Francesco Prendin, Olivia Streicher, Giacomo Cappon, Eva Rolfes, David Herzig, Lia Bally, Andrea Facchinetti

“…In view of this, we developed various algorithms based on linear and deep learning models to forecast PBH episodes in the short-term. …”
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Development and Validation of a Machine Learning Method Using Vocal Biomarkers for Identifying Frailty in Community-Dwelling Older Adults: Cross-Sectional Study by Taehwan Kim, Jung-Yeon Choi, Myung Jin Ko, Kwang-il Kim

“…The SpeechAI model outperformed the model using only demographics significantly in AUC (t4Pt4P ConclusionsOur findings demonstrate that vocal biomarkers derived from deep learning–based acoustic features can be effectively used to predict frailty status in community-dwelling older adults. …”
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Exploring Score-Level and Decision-Level Fusion of Inertial and Video Data for Intake Gesture Detection by Hamid Heydarian, Marc T. P. Adam, Tracy L. Burrows, Megan E. Rollo

“…Recent research has employed deep learning to detect intake gestures from inertial sensor and video camera data. …”
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Explainable Self-Supervised Dynamic Neuroimaging Using Time Reversal by Zafar Iqbal, Md. Mahfuzur Rahman, Usman Mahmood, Qasim Zia, Zening Fu, Vince D. Calhoun, Sergey Plis

“…Objective: Functional magnetic resonance imaging data pose significant challenges due to their inherently noisy and complex nature, making traditional statistical models less effective in capturing predictive features. While deep learning models offer superior performance through their non-linear capabilities, they often lack transparency, reducing trust in their predictions. …”
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Automatic Detection of the Aortic Annular Plane and Coronary Ostia from Multidetector Computed Tomography by Patricio Astudillo, Peter Mortier, Johan Bosmans, Ole De Backer, Peter de Jaegere, Francesco Iannaccone, Matthieu De Beule, Joni Dambre

“…Embedding this tool based on deep learning in the preoperative planning routine may have an impact in the TAVI environments by reducing the time and cost and improving accuracy.…”
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A Structurally Flexible Occupancy Network for 3-D Target Reconstruction Using 2-D SAR Images by Lingjuan Yu, Jianlong Liu, Miaomiao Liang, Xiangchun Yu, Xiaochun Xie, Hui Bi, Wen Hong

“…Driven by deep learning, three-dimensional (3-D) target reconstruction from two-dimensional (2-D) synthetic aperture radar (SAR) images has been developed. …”
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Molecular dynamics and machine learning unlock possibilities in beauty design—A perspective by Yuzhi Xu, Haowei Ni, Fanyu Zhao, Qinhui Gao, Ziqing Zhao, Chia-Hua Chang, Yanran Huo, Shiyu Hu, Yike Zhang, Radu Grovu, Hermione He, John Z. H. Zhang, Yuanqing Wang

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Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study by Salah Bouktif, Akib Mohi Ud Din Khanday, Ali Ouni

“…Two state-of-the-art deep learning approaches (CNN and LSTM) were combined based on features (terms) selected from term frequency–inverse document frequency (TF-IDF), Word2vec, and BERT. …”
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Autoencoder untuk Sistem Prediksi Berat Lahir Bayi by Fitra Septia Nugraha, Hilman Ferdinandus Pardede

“…Penelitian bertujuan untuk prediksi berat lahir bayi menggunakan metode Deep Learning autoencoder untuk memprediksi berat lahir bayi. …”
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Automation of urban technological census. The historical centre of Bethlehem by Elisabetta Doria

“…The proposal is focused on a set of specific elements (water tanks) stacked on the coverings of the historical centre of Bethlehem and leverages close-range photogrammetric acquisitions to train Deep Learning models. The model lifecycle management, from training to prediction and deployment, as well as the storage of both image data and metadata, is performed through the scalability of a Cloud enterprise architecture. …”
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AntiGPS spoofing method for UAV based on LSTM-KF model by Yang SUN, Chunjie CAO, Junxiao LAI, Tianjiao YU

“…A detection method of anti GPS deception of UAV was proposed for the problem that GPS signal of UAV was easy to be interfered and deceived,which combined deep learning and Kalman filter.The dynamic model of UAV flight was predicted from the flight state of UAV by using long short-term memory network,and the dynamic adjustment of Kalman filter and dynamic model was used to identify GPS deception.In order to resist the interference of GPS deception signal,this method did not need to increase the hardware overhead of the receiver,and was easy to realize.The experimental results show that the method has higher accuracy and lower false alarm rate for the recognition of GPS signals,and can effectively enhance the UAV's ability to resist GPS deception interference.…”
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A survey on AI techniques applied in the satellite communication/satellite Internet field by Yaqiong LIU, Zhe LYU, Yafei ZHAO, Guochu SHOU

“…The birth of satellite Internet brings new development opportunities, but also many challenges.How artificial intelligence, as an important auxiliary tool, was widely used in the field of satellite communication/satellite Internet in the context of the development of space-air-ground integration, was investigated, which involved communication anti-jamming, communication routing, satellite-terrestrial network system architecture, constellation operation and management and other scenarios.The AI algorithms included traditional machine learning, deep learning, reinforcement learning and so on.Finally, by taking the development trend of the AI applied in the satellite field into consideration, several future research directions were put forward, which provided new ideas and technical solutions for the intelligent development of satellite field in our country.…”
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Une approche computationnelle du cadastre napoléonien de Venise by Isabella di Lenardo, Raphaël Barman, Federica Pardini, Frédéric Kaplan

“…With the use of digital techniques, based in particular on deep learning, it is now possible to extract from these documents an accurate and dense representation of the city and its inhabitants. …”
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Research on Lung Nodule Detection Based on Improved Target Detection Network by Ye Li, Qian Wu, Hongwei Sun, Xuewei Wang

“…However, in practice, Chinese doctors are likely to cause misdiagnosis. Therefore, deep learning is introduced, an improved target detection network is used, and public datasets are used to diagnose and identify lung nodules. …”
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