Automated software package for selecting transport technology for grain transportation by road freight transport by V. Tsopa, T. Bilko, S. Cheberyachko, O. Deryugin, B. Hrymalo

“…According to the calculation results, it was noted that the transport technology for grain transportation best meets the target indicators – load road train with dump semi-trailer. The dependences of the transport technology for load transportation basic indicators and motor transport enterprise target indicators were established, which allows improving the algorithm for making management decision to choose an effective transport technology for transportation from a set of alternative ones. …”
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Classification of Solar Cells EL Images with Different Busbars Via Deep Learning Models by Miktat Aktaş, İbrahim Türkoğlu, Ferdi Doğan

“…In this study, two AI algorithm and 10 different deep learning models were used to classify solar cells. …”
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ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

“…It is trained using 139 datasets built upon 60 base datasets from 11 diverse domains (finance, healthcare, network security) and 80 ML and DL models composed of 22 base anomaly detection algorithms. …”
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MRI quantified enlarged perivascular space volumes as imaging biomarkers correlating with severity of anxiety depression in young adults with long-time mobile phone use by Li Li, Yalan Wu, Jiaojiao Wu, Bin Li, Rui Hua, Feng Shi, Lizhou Chen, Yeke Wu

“…For classifying depression status, eight features were selected to construct a K nearest neighbors model with an AUC value of 0.931 (95%CI 0.814-1.000) in the testing dataset.DiscussionThe utilization of MRI-quantified EPVS metrics combined with machine-learning algorithms presents a promising method for evaluating severity of anxiety and depression symptoms in patients with LTMPU, which might introduce a non-invasive, objective, and quantitative approach to enhance diagnostic efficiency and guide personalized treatment strategies.…”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…<b>Methods:</b> A U-Net convolutional neural network is trained using preoperative CTA scans, with 101 for model training and 14 for model testing, covering a wide anatomical and aortoiliac pathology spectrum. …”
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Modelling distillate output of a solar distiller with eco-friendly wood-based steam generation basin using machine learning model and starling murmuration optimizer by Mohammed Azmi Al-Betar, Otto L. Muskens, Karrar A. Hammoodi, Mohamed Abd Elaziz, Qusai Yousef Shambour, Salam Fraihat, Ammar H. Elsheikh

“…The predicted data of all models was evaluated using different error measures. These models were standalone LSTM and LSTM optimized by an artificial hummingbird algorithm (AHA) or manta ray foraging optimizer (MRFO). …”
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Emerging trends in sustainable energy system assessments: integration of machine learning with techno-economic analysis and lifecycle assessment by Ebrahimpourboura Zahra, Mosalpuri Manish, Jonas Baltrusaitis, Dubey Pallavi, Mba Wright Mark

“…TEA and LCA methods are enhanced through ML’s predictive modeling, optimization algorithms, and data analysis capabilities, providing more precise and efficient evaluations of SES. …”
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Machine learning insights on activities of daily living disorders in Chinese older adults by Huanting Zhang, Wenhao Zhou, Jianan He, Xingyou Liu, Jie Shen

“…Nine machine learning algorithms, including neural networks and an ensemble model, were employed with a 2/3 training and 1/3 testing split. …”
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Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan by Ahmed Emara, Sameh A. Kantoush, Mohamed Saber, Tetsuya Sumi, Vahid Nourani, Emad Mabrouk

“…The abrasion inventory map, consisting of over 1 million data points indicating damaged and non-damaged sites, was divided equally for training and testing the XGBoost algorithm. Results indicate that the XGBoost model effectively predicts 2D spatial abrasions in SBTs, achieving an overall accuracy of 0.864, exceeding 0.9 in some sections. …”
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High Accuracy of Epileptic Seizure Detection Using Tiny Machine Learning Technology for Implantable Closed-Loop Neurostimulation Systems by Evangelia Tsakanika, Vasileios Tsoukas, Athanasios Kakarountas, Vasileios Kokkinos

“…<b>Methods:</b> A dataset containing iEEG signal values from both non-epileptic and epileptic individuals was utilized for the implementation of the proposed algorithm. Appropriate data preprocessing was performed, and two training datasets with 1000 records of non-epileptic and epileptic iEEG signals were created. …”
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Timeseries Fault Classification in Power Transmission Lines by Non-Intrusive Feature Extraction and Selection Using Supervised Machine Learning by Rab Nawaz, Hani A. Albalawi, Syed Basit Ali Bukhari, Khawaja Khalid Mehmood, Muhammad Sajid

“…Performing specific operations on data in sequence of steps provided flexibility and adaptability in processing the data, making it easy to train, evaluate, and validate the learning algorithms. …”
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Towards a shape-performance integrated digital twin for lumbar spine analysis [version 2; peer review: 2 approved, 1 not approved] by Wei Sun, Xueguan Song, Xiwang He, Xiaonan Lai, Yiming Qiu, Liming Shu, Zhonghai Li

“…Methods A finite element model (FEM) of the lumbar spine was firstly developed using computed tomography (CT) and constrained by the body movement which calculated by the inverse kinematics algorithm. The Gaussian process regression was utilized to train the predicted results and create the digital twin of the lumbar spine in real-time. …”
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TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation by Zekun Jiang, Dongjie Cheng, Ziyuan Qin, Jun Gao, Qicheng Lao, Abdullaev Bakhrom Ismoilovich, Urazboev Gayrat, Yuldashov Elyorbek, Bekchanov Habibullo, Defu Tang, Linjing Wei, Kang Li, Le Zhang

“…The TV-SAM incorporates and integrates the large language model GPT-4, the vision language model GLIP, and the SAM to autonomously generate descriptive text prompts and visual bounding box prompts from medical images, thereby enhancing the SAM’s capability for zero-shot segmentation. Comprehensive evaluations are implemented on seven public datasets encompassing eight imaging modalities to demonstrate that TV-SAM can effectively segment unseen targets across various modalities without additional training. …”
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Development and validation of a prognostic staging system for primary plasma cell leukemia by Mengru Tian, Gang An, Weijun Fu, Wenqiang Yan, Lu Li, Chunyan Sun, Zhenyu Li, Lijuan Chen, Aijun Liao, Guangxun Gao, Xiaoqi Qin, Mengyao Li, Chunrui Li, Hua Xue, Li Gao, Yi Wang, Aili He, Fan Zhou, Dongmei Guo, Yujun Dong, Zhihong Fang, Xiaoxia Chu, Jianqing Mi, Chengcheng Fu, Hui Zeng, Shuling Hou, Xiaotao Wang, Hua Wang, Yongqiang Wei, Xinyue Liang, Xingcheng Yi, Yue Sun, Lugui Qiu, Yun Dai, Fengyan Jin

“…Methods This multicenter retrospective study included 340 patients with pPCL (the training cohort) from 25 centers nationwide in China. …”
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Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records by Aamna AlShehhi, Hiba Alblooshi, Ruba Fadul, Natnael Tumzghi, Amal Al Tenaiji, Mariam Al Harbi, Fatma Al-Jasmi

“…Using nested cross-validation, we trained different feature selection algorithms in combination with various ML algorithms and evaluated their performance with multiple evaluation metrics. …”
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Blending physical and artificial intelligence models to improve satellite-derived bathymetry mapping by Daniel García-Díaz, Sandra Paola Viaña-Borja, Mar Roca, Gabriel Navarro, Isabel Caballero

“…We assessed the ability of these methods to predict bathymetries over successive years subsequent to algorithm calibration, as well as their capacity to estimate depths of other areas not included in model calibration, thereby evaluating temporal and spatial independence, respectively. …”
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Automated AI-based segmentation of canine hepatic focal lesions from CT studies by Silvia Burti, Artur Jurgas, Caterina Puccinelli, Giunio Bruto Cherubini, Simonetta Citi, Alessandro Zotti, Marek Wodziniski, Marek Wodziniski, Rachele Brusco, Emma Quaresima, Martina Giordano, Margherita Bendazzoli, Diane Wilson, Nicolò Mastromattei, Tommaso Banzato

“…Experienced veterinarians manually segmented the lesions to provide ground truth data. 25/200 CTs were excluded because they did not met the inclusion criteria. Finally, the algorithm was built using the nnUNet v2 framework and trained on 130 cases with a 5-fold training scheme. …”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…Experimental evaluations on the Kvasir-V1 and Kvasir-V2 datasets demonstrate superior performance, achieving accuracies of 99.60% and 95.10%, respectively. …”
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Pixel-Based Long-Wave Infrared Spectral Image Reconstruction Using a Hierarchical Spectral Transformer by Zi Wang, Yang Yang, Liyin Yuan, Chunlai Li, Jianyu Wang

“…Recent advancements in computational spectral imaging, powered by advanced algorithms, have enabled the acquisition of high-quality spectral images in real time, such as with the Uncooled Snapshot Infrared Spectrometer (USIRS). …”
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Congo red fluorescence enhances digital pathology workflow in cardiac amyloidosis by Giorgio Cazzaniga, Monica De Gaspari, Vincenzo L’Imperio, Carlo Beretta, Angela Greco, Stefania Rizzo, Cristina Basso, Fabio Pagni

“…The diagnostic performance of CRF on virtual slides was evaluated in a cohort of EMB and autopsy cases. The feasibility of developing AI algorithms applicable to centers lacking a fluorescence scanner was investigated leveraging a computational pipeline that enables fluorescence outcome visualization in brightfield. …”
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