Open-sourced modeling and simulating tools for decision-makers during an emerging pandemic or epidemic – Systematic evaluation of utility and usability: A scoping review update by Rebecca Sophia Lais, Julia Fitzner, Yeon-Kyeng Lee, Verena Struckmann

“…Emerging infectious diseases and pandemics will persist as a global health threat and preparedness for an evidence based response becomes challenging for decision makers. …”
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AppAuth: Authorship Attribution for Android App Clones by Guoai Xu, Chengpeng Zhang, Bowen Sun, Xinyu Yang, Yanhui Guo, Chengze Li, Haoyu Wang

“…AppAuth first extracts a number of coding-style-related features from the executable <italic>.apk</italic> files, and then relies on machine learning techniques to train a classification model. …”
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Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT by Emanuele Trucco, Joanna M Wardlaw, Wenwen Li, Grant Mair, Amos Storkey, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt, Paul Armitage

“…Our algorithm was trained using routinely acquired CT brain scans collected for a large multicentre international trial. …”
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Guidance strategies for infantile asymmetry prevention: a systematic review by Julie Ellwood, Kesava Kovanur Sampath, Iryna Rund, Loïc Treffel, Jerry Draper-Rodi

“…Coincidence in the presentation of asymmetrical features can lead to a broad spectrum of descriptors. …”
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Use of Vision Transformer to Classify Sea Surface Phenomena in SAR Imagery by Junfei Xia, Roland Romeiser, Wei Zhang, Tamay Ozgokmen

“…This comparative analysis also underscores the limitations of CNNs, which perform well on texture-based features but struggle with structural classifications, such as rain cells and oceanic fronts, where ViTs excel. …”
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Mental Health and Well‐Being Support for Individuals Living With Skin Conditions: A Global Landscape Analysis of Patient Needs and Current Resources by Tammi Shipowick, Jennifer Austin, Nicole Sudiacal, Stephanie Miller, Jennifer A. Pereira, Christine Bundy

“…In regions such as Africa, and remote and rural Western Pacific, task‐shifting, a process whereby laypeople are trained by health professionals to deliver community‐based interventions, may be a promising format given mental health professional shortages. …”
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Machine learning-assisted image analysis techniques for glaucoma detection by Vaibhav Yadav, Barnali Dey, Udayan Baruah, Saumya Das, Om Prakash

“…These techniques mainly focused on standard retinal image datasets to train the model and demonstrated good detection accuracy. …”
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AutoTarget: Disease-Associated druggable target identification via node representation learning in PPI networks by Hyunseung Kong, Inyoung Kim, Byoung-Tak Zhang

“…However, limitations were noted, including the inability to distinguish between different types of disease-associated proteins based solely on network features. Overall, this study advances the application of machine learning and network theory for identifying druggable targets across a wide range of diseases. …”
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Enhancing prediction of fluid-saturated fracture characteristics using deep learning super resolution by Manju Pharkavi Murugesu, Vignesh Krishnan, Anthony R. Kovscek

“…There is a trade-off between spatial and temporal resolution that limits accurate characterization of dynamics in rock features that are below spatial resolution of CT. While past literature has offered solutions to improve resolution of CT rock images, including deep learning-based algorithms, our study uniquely focuses on improving dynamic, partially and fully fluid-saturated geological images. …”
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Artificial Intelligence and Novel Technologies for the Diagnosis of Upper Tract Urothelial Carcinoma by Nikolaos Kostakopoulos, Vasileios Argyropoulos, Themistoklis Bellos, Stamatios Katsimperis, Athanasios Kostakopoulos

“…<i>Results</i>: Artificial intelligence systems have been shown to enhance post-radical nephroureterectomy urine cytology reporting, in order to facilitate the early diagnosis of bladder recurrence, as well as improve diagnostic accuracy in atypical cells, by being trained on annotated cytology images. In addition to this, by extracting textural radiomics features from data from computed tomography urograms, we can develop machine learning models to predict UTUC tumour grade and stage in small-size and especially high-grade tumours. …”
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Artificial Intelligence Approach in Hip Prosthesis Identification and Addressing Radiographic Outcome Measures by Omar Musbahi, MSc, ChM, Savvas Hadjixenophontos, MEng, Saran S. Gill, Iris Soteriou, Bsc, Kyriacos Pouris, Bsc, Takuro Ueno, PhD, Justin P. Cobb, MCh

“…A neural network (NN) was then trained using clinician-generated AP radiograph NSAs as ground truths and AI-generated AP and lateral NSAs as features. …”
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DCE-YOLOv8: Lightweight and Accurate Object Detection for Drone Vision by Jinsu An, Dong Hee Lee, Muhamad Dwisnanto Putro, Byeong Woo Kim

“…To effectively detect small objects, it is imperative to either enhance the resolution of drone images or efficiently extract the features of small objects. Additionally, the efficient integration of these extracted features is crucial. …”
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Ultralow Saturation Intensity Topological Insulator Saturable Absorber for Gigahertz Mode-Locked Solid-State Lasers by Yi-Ran Wang, Wei-Heng Sung, Xian-Cui Su, Yue Zhao, Bai-Tao Zhang, Chung-Lung Wu, Guan-Bai He, Yuan-Yao Lin, Hong Liu, Jing-Liang He, Chao-Kuei Lee

“…The successful demonstration of Q-switched and mode-locked fiber-laser operations using a topological insulator (TI) as saturable absorber (SA) has opened an application window besides TI&#x0027;s originally expected features. However, to date, all-solid-state mode-locked lasers base on TISAs are still unavailable and became a desired goal not only due to their application as light sources, but also because of providing a way for deeper investigation of the nature of ultrafast dynamics present in TISAs. …”
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Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks by Chamalka Kenneth Perera, Alpha. A. Gopalai, Darwin Gouwanda, Siti. A. Ahmad, Pei-Lee Teh

“…STW itself can be generalized into strategies based on individual needs and movement patterns. …”
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Enhanced U-Net for Underwater Laser Range-Gated Image Restoration: Boosting Underwater Target Recognition by Peng Liu, Shuaibao Chen, Wei He, Jue Wang, Liangpei Chen, Yuguang Tan, Dong Luo, Wei Chen, Guohua Jiao

“…Built upon the U-Net architecture with added residual connections, our network combines a VGG16-based perceptual loss with Mean Squared Error (MSE) as the loss function, effectively capturing high-level semantic features while preserving critical target details during reconstruction. …”
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The Residents\' Experiences of Physical Integration in Settlement Developments: A Case Study of Historical Village of Qahi by Azadeh Lak, Eftekhar Azizkhani

“…The rural development has been implemented based on urban development plans in the form of contemporary urban grid pattern which is at odds with the organic pattern of the village. …”
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Interventions to improve mental health and well-being in care-experienced children and young people aged less than 25: the CHIMES systematic review by Rhiannon Evans, Sarah MacDonald, Robert Trubey, Jane Noyes, Michael Robling, Simone Willis, Soo Vinnicombe, Maria Boffey, Charlotte Wooders, Asmaa El-Banna, GJ Melendez-Torres

“…Objectives The CHIMES review is a complex-systems-informed mixed-method systematic review that aimed to synthesise the international evidence base for interventions addressing the mental health and well-being of care-experienced children and young people (age ≤ 25 years) and to assess the potential transportability of this evidence base to the United Kingdom context. …”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…The final model, refined to include nine essential features, achieved an AUC of 0.787 (95%CI 0.670–0.883). …”
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Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

“…Accuracy in rail transit station classification is critical, as it not only strengthens the model’s predictive capabilities but also ensures more reliable data-driven decisions for transit planning and development, allowing for more precise ridership forecasts and evidence-based strategies for optimizing TOD. This classification model provides stakeholders with valuable insights into the dynamics and features of rail transit stations, supporting sustainable urban development planning.…”
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Coastal salt marsh vegetation classification using hybrid convolutional neural networks and spectral index time series images by Bolu Sun, Dong Zhang, Zhengqing Lai

“…The hybrid model integrates 2D-3D convolutions to extract spatial features and fully capture temporal dynamics, enabling accurate classification. …”
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