Artificial Intelligence–Aided Diagnosis System for the Detection and Classification of Private-Part Skin Diseases: Decision Analytical Modeling Study by Wei Wang, Xiang Chen, Licong Xu, Kai Huang, Shuang Zhao, Yong Wang

“…Compared with existing advanced algorithms, this system is more accurate in identifying PPSDs. …”
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Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: A multi-reader study by Tommaso Di Noto, Sofyan Jankowski, Francesco Puccinelli, Guillaume Marie, Sebastien Tourbier, Yasser Alemán-Gómez, Oscar Esteban, Ricardo Corredor-Jerez, Guillaume Saliou, Patric Hagmann, Meritxell Bach Cuadra, Jonas Richiardi

“…Despite the plethora of AI-based algorithms developed for anomaly detection in radiology, subsequent integration into clinical setting is rarely evaluated. …”
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An innovative methodology for segmenting vessel like structures using artificial intelligence and image processing by Reynaldo Villarreal, Sindy Chamorro-Solano, Steffen Cantillo, Roberto Pestana-Nobles, Sair Arquez, Yolanda Vega-Sampayo, Leonardo Pacheco-Londoño, Jheifer Paez, Nataly Galan-Freyle, Cristian Ayala, Paola Amar

“…This is achieved by training algorithms to detect specific pixels, thereby recognizing details within images. …”
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Comparative performance of twelve machine learning models in predicting COVID-19 mortality risk in children: a population-based retrospective cohort study in Brazil by Adriano Lages dos Santos, Maria Christina L. Oliveira, Enrico A. Colosimo, Robert H. Mak, Clara C. Pinhati, Stella C. Gallante, Hercílio Martelli-Júnior, Ana Cristina Simões e Silva, Eduardo A. Oliveira

“…Using these subsets, we developed and trained 12 ML algorithms to predict the outcomes. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…Feature selection included an initial screening for multicollinearity using correlation-based feature pruning, followed by final selection using a genetic algorithm. Feature importance was evaluated using permutation importance and SHAP values. …”
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L2R-MLP: a multilabel classification scheme for the detection of DNS tunneling by Emmanuel Oluwatobi Asani, Mojiire Oluwaseun Ayoola, Emmanuel Tunbosun Aderemi, Victoria Oluwaseyi Adedayo-Ajayi, Joyce A. Ayoola, Oluwatobi Noah Akande, Jide Kehinde Adeniyi, Oluwambo Tolulope Olowe

“…L2 regularization in the MLP classifier's hidden layers enhances pattern recognition during training, effectively countering the risk of overfitting. …”
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Development and validation of a nomogram for predicting in-hospital mortality in older adult hip fracture patients with atrial fibrillation: a retrospective study by Zhenli Li, Jing He, Tiezhu Yao, Guang Liu, Jing Liu, Ling Guo, Mengjia Li, Mengjia Li, Zhengkun Guan, Zhengkun Guan, Ruolian Gao, Jingtao Ma

“…The nomogram exhibited superior predictive performance (AUC:0.834) than conventional scoring systems in the training set, with an AUC of 0.715 in external validation.ConclusionOur study constructed a predictive model based on features selected by machine learning approaches to evaluate the in-hospital mortality risk of critically ill patients with hip fractures combined with AF. …”
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Diagnosing facial synkinesis using artificial intelligence to advance facial palsy care by Leonard Knoedler, Christian Festbaum, Jillian Dean, Helena Baecher, Grégoire de Lambertye, Maximilian Maul, Thomas Schaschinger, Tobias Niederegger, Alexandra Scheiflinger, Michael Alfertshofer, Khalil Sherwani, Claudius Steffen, Max Heiland, Steffen Koerdt, Samuel Knoedler, Andreas Kehrer

“…A total of 385 images were used to train and evaluate a convolutional neural network (CNN). …”
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Simulation-Based Analysis of DRL Exploitation Rate for Voltage and Frequency Stability in a Single-Inverter Microgrid Control System by Noer Fadzri Perdana Dinata, Makbul Anwari Muhammad Ramli, Muhammad Irfan Jambak, Prisma Megantoro, Muhammad Abu Bakar Sidik

“…This paper discusses the development and performance evaluation of a single-inverter-based microgrid control system using a Deep Reinforcement Learning (DRL) agent trained with the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. …”
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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…Multiple machine learning algorithms were trained using this dataset, exhibiting promising performance. …”
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Texture Analysis of T2-Weighted Images as Reliable Biomarker of Chronic Kidney Disease Microstructural State by Marcin Majos, Artur Klepaczko, Katarzyna Szychowska, Ludomir Stefanczyk, Ilona Kurnatowska

“…The aim of this study is to create an algorithm that can categorize CKD patients into active and non-active phases on the basis of MRI texture analysis and compare the results with histopathological examinations. …”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…Machine learning (ML) models were also created in order to predict compressive strength based on mix composition and curing age using Orange Data Mining software version 3.36. Five algorithms: KNN, Support Vector Machine (SVM), Artificial Neural Networks (ANN), Decision Tree (DT), and Random Forest (RF), were trained and evaluated. …”
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Predicting the infecting dengue serotype from antibody titre data using machine learning. by Bethan Cracknell Daniels, Darunee Buddhari, Taweewun Hunsawong, Sopon Iamsirithaworn, Aaron R Farmer, Derek A T Cummings, Kathryn B Anderson, Ilaria Dorigatti

“…Model performance was calculated using 100 bootstrap samples of the train and out-of-sample test sets. Our analysis showed that, on average, the greatest change in titre was against the infecting serotype. …”
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Radiomics machine learning based on asymmetrically prominent cortical and deep medullary veins combined with clinical features to predict prognosis in acute ischemic stroke: a retr... by Hongyi Li, Cancan Chang, Bo Zhou, Yu Lan, Peizhuo Zang, Shannan Chen, Shouliang Qi, Ronghui Ju, Yang Duan

“…An APCV-DMV radiomic model was created via the SVM algorithm, and independent clinical risk factors associated with AIS were combined with the radiomic model to generate a joint model. …”
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Experiments on Improving Temperature and Humidity Profile Retrieval for Ground-based Microwave Radiometer by Zhang Xuefen, Wang Zhicheng, Mao Jiajia, Wang Zhangwei, Zhang Dongming, Tao Fa

“…Many studies show that different seasons, different weather conditions, quality control algorithms, and changes in environments have certain effects on retrieval results of MWR. …”
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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

“…The study collected 86 lung cancer patients who received CK′s built-in MC algorithm plans using different beam configurations for training/validation (66 cases) and testing (20 cases). …”
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A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching by Jose Moises Araya-Martinez, Jose Moises Araya-Martinez, Vinicius Soares Matthiesen, Vinicius Soares Matthiesen, Simon Bøgh, Jens Lambrecht, Rui Pimentel de Figueiredo

“…Moreover, they usually involve the collection and labeling of large training datasets, which is costly and time-consuming. …”
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Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions by Elif Yavuz, Alihan Öztürk, Nedime Gaye Nur Balkanlı, Şeref Naci Engin, S. Levent Kuzu

“…Machine learning has significantly advanced traffic surveillance and management, with YOLO (You Only Look Once) being a prominent Convolutional Neural Network (CNN) algorithm for vehicle detection. This study utilizes YOLO version 7 (YOLOv7) combined with the Kalman-based SORT (Simple Online and Real-time Tracking) algorithm as one of the models used in our experiments for real-time vehicle identification. …”
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Construction of a Prediction Model for Sleep Quality in Embryo Repeated Implantation Failure Patients Undergoing Assisted Reproductive Technology Based on Machine Learning: A Singl... by Zhao Y, Xu C, Qin N, Bai L, Wang X, Wang K

“…Use Lasso regression to screen variables and construct a risk prediction model using six machine learning algorithms. Evaluate the validity of the model using the area under the curve (AUC), and comprehensively evaluate the performance of the model based on F1 score, accuracy, sensitivity, and specificity. …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…Several machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, Random Forests, and Neural Networks, were implemented and evaluated. …”
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