Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…What impacts on the prognosis of anorexia nervosa: the implication for staging anorexia nervosa The project would combine existing databases from trials and clinical electronic records to determine prognostic features and possible staging models for AN. Support for the diversity of carers of eating disorders (fathers, partners, siblings) in different cultural contexts across the spectrum of eating disorders The current model of carers support is designed for parents (particularly mothers) of white, highly educated patients with AN. …”
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Post-Disaster Building Damage Segmentation Using Convolutional Neural Networks by Revaldi Rahmatmulya, Agung Teguh Wibowo Almais, Mokhamad Amin Hariyadi

“…This study proposes an architecture with 27 hidden layers, with feature extraction utilizing average pooling. The model evaluation process will employ Mean Intersection over Union (MIoU) to assess how closely the segmentation prediction results resemble the original data. …”
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Hydra-Mask-RCNN: An Adaptive HydraNet Architecture for Autonomous Aerial Vehicle Object Detection by Sara Naseri Golestani, Mahdi SadeghiBakhi, King Fai Ma, Henry Leung

“…By integrating an adaptive branching network (ABN) with HydraNet, HMRCNN improves feature extraction and object detection capabilities. …”
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Current status of artificial intelligence analysis for the treatment of pancreaticobiliary diseases using endoscopic ultrasonography and endoscopic retrograde cholangiopancreatogra... by Takamichi Kuwahara, Kazuo Hara, Nobumasa Mizuno, Shin Haba, Nozomi Okuno, Toshitaka Fukui, Minako Urata, Yoshitaro Yamamoto

“…Future advances in AI, such as large language models, promise further applications in the medical field.…”
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Degrade or Super-Resolve to Recognize? Bridging the Domain Gap for Cross-Resolution Face Recognition by Klemen Grm, Berk Kemal Ozata, Alperen Kantarci, Vitomir Struc, Hazim Kemal Ekenel

“…Our results show that the combination of standard computer vision approaches such as degradation, super-resolution, feature fusion, and score fusion can be used to substantially improve performance on the task of low resolution face recognition using off-the-shelf face recognition models without re-training on the target domain.…”
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Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms by Zhong-Han Zhuang, Hui-Ping Tsai, Chung-I Chen

“…However, PRI and ΦPSII values revealed greater environmental adaptability and potential long-term ecological benefits in AFMs compared to CFMs. Among regression models, MIs provided greater stability for tea plant physiological parameters, whereas feature ranking methods had minimal impact on accuracy. …”
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DeepMoIC: multi-omics data integration via deep graph convolutional networks for cancer subtype classification by Jiecheng Wu, Zhaoliang Chen, Shunxin Xiao, Genggeng Liu, Wenjie Wu, Shiping Wang

“…Conclusion The introduction of Deep GCN shows encouraging performance in terms of supervised multi-omics feature learning, offering promising insights for precision medicine in cancer research. …”
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NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

“…Three principal innovations are introduced: (1) a hardware-compatible sparse attention architecture achieving O(n) computational complexity while preserving high-fidelity geological feature extraction capabilities; (2) an adaptive kernel function optimization mechanism that reduces confidence interval width by 41.3% through synergistic integration of boundary likelihood-driven kernel selection with Chebyshev inequality-based posterior estimation; and (3) a physics-enhanced modelling methodology combining non-Hertzian contact mechanics with eddy field evolution equations. …”
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Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis. by Rodolfo Rossi, Stanley Zammit, Katherine S Button, Marcus R Munafò, Glyn Lewis, Anthony S David

“…The independent variable was performance on a computerized numerical n-back working memory task. …”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…This work underscores the feasibility of deploying resource-efficient AI models in environments where traditional high-performance computing resources are unavailable, typically in healthcare settings, paving the way for and contributing to advanced computer vision techniques in embedded systems.…”
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Emotion Classification from Electroencephalographic Signals Using Machine Learning by Jesus Arturo Mendivil Sauceda, Bogart Yail Marquez, José Jaime Esqueda Elizondo

“…Compared to state-of-the-art methods, such as ResNet18 combined with differential entropy, which achieved 95.61% accuracy on the same dataset, the tested models demonstrated substantial limitations. Conclusions: Our results highlight the challenges of generalizing across emotional states using raw EEG signals, emphasizing the need for advanced preprocessing and feature-extraction techniques. …”
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Automatic Subject Cataloguing at the German National Library by Christoph Poley, Sandro Uhlmann, Frank Busse, Jan-Helge Jacobs, Maximilian Kähler, Matthias Nagelschmidt, Markus Schumacher

“…A brief report is given about the construction and the performance of our models. Based on these use cases, we present some implementation aspects of our “subject cataloguing machine” EMa, the environment for automatic subject cataloguing in productive use. …”
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Microstrip Patch Sensor for Characterizing Saline Solution Based on Complimentary Split-Ring Resonators (SC-SRRs) by Hussein Jasim, Sadiq Ahmed, Iulia Andreea Mocanu, Amer Abbood Al-Behadili

“…This article presents a novel microstrip patch sensor featuring four rectangular rings represented by single complementary split-ring resonance (SC-SRR) to calculate the complex permittivity of saline solutions within the range of 0 ppt to 100 ppt. …”
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Prevalence of physiological and perceptual markers of low energy availability in male academy football players: a study protocol for a cross-sectional study by Philip Smith, Nick Dobbin, John P Rogers, Jamie Ashby, Thomas Mullen

“…Low energy availability (LEA) is a core feature of the female athlete triad and relative energy deficiency in sport (REDs). …”
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Body-part-based individual feral cat identification from camera trap images using deep learning by Rio Rifqi Syah Akbar, Matthew W. Rees, Patricia A. Fleming, Ferdous Sohel

“…We trained deep-learning models with a ResNet-50 backbone on these body parts indivdually as well as combinations of multiple body parts through feature concatenation. …”
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Optimal design of renewable driven polygeneration system: A novel approach integrating TRNSYS-GenOpt linkage by Muhammad Shoaib Saleem, Naeem Abas

“…The system is modeled and simulated using TRNSYS® and optimized via GenOpt by applying Hooke-Jeeve's algorithm. …”
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Plasma lipidomic analysis reveals disruption of ether phosphatidylcholine biosynthesis and facilitates early detection of hepatitis B-related hepatocellular carcinoma by Yuyao Yuan, Donghao Yin, Xuemeng Yang, Di Liu, Hui Shan, Juan Luo, Xiuhui Li, Yuxin Yin

“…A machine learning algorithm is used for feature selection and diagnostic modelling, and performance of the models is evaluated by ROC curves. …”
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Preparticipation screening in young female elite ice hockey players by Alexander Mohl, Janis Pongratz, Selina Muxel, Manuel Berger, Michael Berr, Michael Berr, Bastian Schneider, Anna Schlichting-Knoob, Ulrich Platz, Ulrich Platz, Uwe Dorwarth, Sebastian Rogowski, Ellen Hoffmann, Florian Straube

“…ObjectivesThe occurrence of sudden cardiac death (SCD) in competitive athletes has led to a discussion about appropriate preparticipation screening models. The role of an electrocardiogram (ECG) in routine testing remains controversial in current guidelines. …”
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Diagnosis of Coronary Heart Disease Through Deep Learning-Based Segmentation and Localization in Computed Tomography Angiography by Bo Zhao, Jianjun Peng, Ce Chen, Yongyan Fan, Kai Zhang, Yang Zhang

“…Trained and evaluated on the CorArtTS2020 dataset, TransCHD achieved superior performance compared to state-of-the-art CNN- and transformer-based models, with a Dice score of 0.81 and an Intersection over Union (IoU) of 0.65. …”
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Development of Quantitative Structure–Anti-Inflammatory Relationships of Alkaloids by Cristian Rojas, Doménica Muñoz, Ivanna Cordero, Belén Tenesaca, Davide Ballabio

“…The performance of the models was quantified by means of the non-error rate (<i>NER</i>) statistical parameter.…”
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