Risk stratification in neuroblastoma patients through machine learning in the multicenter PRIMAGE cohort by Jose Lozano-Montoya, Ana Jimenez-Pastor, Almudena Fuster-Matanzo, Glen J. Weiss, Leonor Cerda-Alberich, Diana Veiga-Canuto, Blanca Martínez-de-Las-Heras, Blanca Martínez-de-Las-Heras, Adela Cañete-Nieto, Sabine Taschner-Mandl, Barbara Hero, Thorsten Simon, Ruth Ladenstein, Luis Marti-Bonmati, Luis Marti-Bonmati, Angel Alberich-Bayarri

“…IntroductionNeuroblastoma, the most prevalent solid cancer in children, presents significant biological and clinical heterogeneity. …”
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Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

“…The adaptive generation of multiple NC processes for a new subpart is presented. The previous 3D model retrieval method retrieves and returns similar subpart instances with their NC processes. …”
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RehabHand—A New Physical Rehabilitation Training Dataset: Construction and Benchmark Performances of the Relevant Hand Tasks by Sinh Huy Nguyen, Hoang Bach Nguyen, Thi Thu Hong Le, Chi Thanh Nguyen, Thi Thanh Huyen Nguyen, Quynh Tho Chu, Thi Lan Le, Thanh Hai Tran, Hai Vu

“…These videos are segmented into 431 sequences that present instances of each exercise at a certain time. …”
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Automated Detection of High Frequency Oscillations in Intracranial EEG Using the Combination of Short-Time Energy and Convolutional Neural Networks by Dakun Lai, Xinyue Zhang, Kefei Ma, Zichu Chen, Wenjing Chen, Heng Zhang, Han Yuan, Lei Ding

“…The proposed methodology presents the following significant advantages: 1) compared with the recently reported HFOs detector based on the CNN using only the 1D temporal EEG signal, the proposed method achieves a higher accuracy using the deep CNN classifier on 2D time–frequency map of HFOs, of which the evaluated sensitivity and false discovery rate (FDR) for identifying ripples are 88.16% and 12.58%, respectively, and the corresponding sensitivity and FDR are 93.37% and 8.1% for detecting fast ripples, respectively; 2) it is capable of automatically extracting the shared features of HFOs events of different patients and would be much robust, unlike other automated methodologies proposed in the literature where the characteristics of HFOs were extracted manually on the basis of researchers’ knowledge, which, probably, is prone to observer bias; and 3) with the proposed STE estimation, all suspicious ripples and fast ripples could be initially found out and transformed into time–frequency map for subsequently CNN-based classification, rather than transforming and classifying the raw data, thus requiring a lower computational resource. …”
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High-Performance On-Orbit Intelligent Computing and Real-Time Services for Remote Sensing Satellites Based on Large-Scale Computing Power in Space by Guoping Wang, Gang Wan, Zhijuan Su, Yang Wang, Yutong Jia, Gong Li, Shi Liang

“…The onboard-distributed processing framework can be leveraged to fully utilize wide-area scattered space computing resources; accordingly, it is possible to automatically establish a network of neighboring satellites through inter-satellite communication links to construct a spatially distributed and computationally cooperative cloud computing environment in space. …”
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Is the fluorescence optical imaging (FOI) able to discriminate between rheumatoid arthritis patients with and without need of rituximab retherapy? A cohort study by Sandra Hermann, Gerd R Burmester, Sarah Ohrndorf, Marina Backhaus, Paula Hoff, Jens Klotsche, Anne-Marie Glimm, Schahrasad Lisa Ridha Ali, Gabriela Schmittat

“…In the group with RTX retherapy, FOI in PVM mode was the only parameter that presented significant increase over time (β: 0.40, 95% CI: 0.08 to 0.71, p=0.013)—compared with the group without retherapy. …”
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Automated dairy cow identification and feeding behaviour analysis using a computer vision model based on YOLOv8 by Claudia Giannone, Mohsen Sahraeibelverdy, Martina Lamanna, Damiano Cavallini, Andrea Formigoni, Patrizia Tassinari, Daniele Torreggiani, Marco Bovo

“…The promising results presented here contribute to the advancement and validation of computer vision applications in herd monitoring, supporting the commercial adoption of these technologies for analysing cow behaviour so increasing animal welfare and the sustainability of the animal production.…”
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Enabling high-throughput quantitative wood anatomy through a dedicated pipeline by Jan Van den Bulcke, Louis Verschuren, Ruben De Blaere, Simon Vansuyt, Maxime Dekegeleer, Pierre Kibleur, Olivier Pieters, Tom De Mil, Wannes Hubau, Hans Beeckman, Joris Van Acker, Francis wyffels

“…Finally, a Python routine using a trained YOLOv8 deep learning network allows for fully automated analysis of the gigapixel images, here shown as a proof-of-concept for the quantification of vessels and rays on full disc surfaces and increment cores. We present fully digitized beech discs of 30–35 cm diameter at a resolution of 2.25  $$\upmu$$ μ m, for which we automatically quantified the number of vessels (up to 13 million) and rays. …”
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Computed tomography-based radiomics prediction model for differentiating invasive pulmonary aspergillosis and Pneumocystis jirovecii pneumonia by Zhiguo Peng, Xingzhe Gao, Miao He, Xinyue Dong, Dongdong Wang, Zhengjun Dai, Dexin Yu, Huaibin Sun, Jun Tian, Yu Hu

“…All the patients were randomly divided into two cohorts, training and validation, at a ratio of 7:3 using random seeds automatically generated using the RadCloud platform. …”
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Zero‐shot insect detection via weak language supervision by Benjamin Feuer, Ameya Joshi, Minsu Cho, Shivani Chiranjeevi, Zi Kang Deng, Aditya Balu, Asheesh K. Singh, Soumik Sarkar, Nirav Merchant, Arti Singh, Baskar Ganapathysubramanian, Chinmay Hegde

“…Our method succeeds in detecting diverse insect species present in a wide variety of backgrounds, producing high‐quality bounding boxes in a zero‐shot manner with no additional training cost. …”
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A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes by J. Li, A. Geiss, Z. Feng, L. R. Leung, Y. Qian, W. Cui, W. Cui

“…Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study presents an objective derecho detection approach capable of automatically identifying derechos through both observations and model results. …”
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Dataset for legal question answering system in the Indian judiciary contextMendeley Data by Veningston K, Apratim Mishra

“…Due to the lack of a relevant dataset for an LQA system [3], this paper presents a comprehensive dataset designed for LQA in the Indian judiciary context that facilitates efficient legal information retrieval. …”
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Using WhatsApp for Nutrition Surveillance Among Children Under 5 Years in West Java, Indonesia: Cross-Sectional Survey and Feasibility Study by Dewi Nur Aisyah, Chyntia Aryanti Mayadewi, Astri Utami, Fauziah Mauly Rahman, Nathasya Humaira Adriani, Erlangga Al Farozi, Meldi Hafizh Sayoko, Aulia Chairunisa, Liza Restiana, Logan Manikam, Zisis Kozlakidis

“…The anthropometric measurement data were reported in real time through a WhatsApp chatbot, automatically analyzed by the system, and presented in a structured dashboard. …”
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Analysing Open-source Images to Assess Face Mask Usage for Epidemiological Studies by Dr Hang Ding, Mrs Ashley Quigley, Professor Raina MacIntyre

“…This study aims to develop and validate an Artificial Intelligence (AI) solution to automatically analyse open-source crowd photos for estimation of mask use. …”
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A Chisel Generator for Standardized 3-D Die-to-Die Interconnects by Harrison Liew, Farhana Sheikh, Jong-Ru Guo, Zuoguo Wu, Borivoje Nikolic

“…Technology-driven constraints highlighted in published works demonstrate that a unique approach to 3-D D2D interconnect design and implementation is required, while preserving the ability to customize the interconnect to accommodate future technology concerns and applications with minimal overhead. This article presents a framework to generate customized 3-D D2D interconnect physical layers (PHYs) that are simultaneously standard-compliant, physical-aware, and can be automatically integrated into all stacked chiplets. …”
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Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm by Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb

“…APSO-CNN uses the global search capabilities of Particle Swarm Optimization (PSO) to automatically optimize hyperparameter configurations for architecture-determined Convolutional Neural Networks (CNNs). …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…Because these methods can automatically extract meaningful features from data and efficiently learn complex relationships, they can achieve better performance in malware detection as well as in solving many other problems. …”
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Transformers for Domain-Specific Text Classification: A Case Study in the Banking Sector by Samer Murrar, Fatima M. Alhaj, Fadi Almasalha, Mahmoud H. Qutqut

“…With AI integration, the system now categorizes messages automatically and in real time, ensuring that relevant department managers receive them promptly, significantly improving operational workflows. …”
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A 10-Meter Active Optical Cable Utilizing POF With 4 × 10-Gb/s CMOS Transceiver Chipsets by Chaerin Hong, Seung-Hoon Kim, Sangmo Cha, Sung Min Park

“…Also, a novel input data detector is proposed to turn <sc>on&#x002F;off</sc> VCSEL diodes automatically for longer sustainability and lower power consumption. …”
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Self-adaptation of e-learning software based on observing the information environment by A. M. Bershadskiy, A. S. Bozhday, A. A. Gudkov, Yu. I. Evseeva

“…The configuration of the model of characteristics is a separate state of the self-adaptive system, they are generated automatically during the program’s life cycle as follows: based on an array of user reviews, a semantic network of basic concepts characterizing the program is formed, which is further compared with the original model of characteristics and personal characteristics of the user who left review. …”
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