Convolutional neural network-based diagnosis of the relationship between mandibular third molar and mandibular nerve canal by ZHANG Jinping, YU Xian, CHEN Yiming, WANG Zehui, TAO Yu, WEI Yi, LI Birong, ZHU Bingzhen, ZHANG Juan

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Association between life’s crucial 9 and lung health: a population-based study by Haolin Shi, Xiuhua Ma

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The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population–Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis... by Musa Jaiteh, Edith Phalane, Yegnanew A Shiferaw, Refilwe Nancy Phaswana-Mafuya

“…ObjectiveThis study aims to determine consistent predictors of HIV testing by applying supervised ML algorithms in repeated adult population-based surveys in South Africa. MethodsA retrospective analysis of multiwave cross-sectional survey data will be conducted to determine the predictors of HIV testing among South African adults aged 18 years and older. …”
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Kerja lapangan dan simulasi peradilan sebagai metode pembelajaran mata kuliah Hukum Administrasi Negara by Eny Kusdarini, Setiati Widihastuti

“…Based on the explanation above, this research has an objective to develop the field work method and the fictive justice functioned as the learning model of State Administration Law subject in Department of Civic Education and Law (PKnH) FISE UNY which applies student centered learning characteristic. …”
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Effectiveness of a school-based programme of animal-assisted humane education in Hong Kong for the promotion of social and emotional learning: A quasi-experimental pilot study. by Joe T K Ngai, Rose W M Yu, Kathy K Y Chau, Paul W C Wong

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Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population. by John T Murchison, Gillian Ritchie, David Senyszak, Jeroen H Nijwening, Gerben van Veenendaal, Joris Wakkie, Edwin J R van Beek

“…Sensitivity, false positive (FP) rate and Dice inter-reader coefficient were calculated.…”
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Simulation of Active Layer Thickness Based on Multi-Source Remote Sensing Data and Integrated Machine Learning Models: A Case Study of the Qinghai-Tibet Plateau by Guoyu Wang, Shuting Niu, Dezhao Yan, Sihai Liang, Yanan Su, Wei Wang, Tao Yin, Xingliang Sun, Li Wan

“…Additionally, the SCE model was verified via ten-fold cross-validation (MAE: 20.713 cm, RMSE: 32.680 cm, R²: 0.873, and MAPE: 0.104), and its inversion of QTP’s ALT data from 1958 to 2022 revealed 1998 as a key turning point with a slow growth rate of 0.25 cm/a before 1998 and a significantly increased rate of 1.26 cm/a afterward. Finally, based on multiple model input factor analysis methods (SHAP, Pearson correlation, and Random Forest Importance), the study analyzed the ranking of key factors influencing ALT changes. …”
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Performance of chest X-ray with computer-aided detection powered by deep learning-based artificial intelligence for tuberculosis presumptive identification during case finding in t... by Nichel Marquez, Erwin John Carpio, Mary Rosary Santiago, Jeremiah Calderon, Ruth Orillaza-Chi, Shawnee Shaine Salanap, Lisa Stevens

“…Systematic TB case finding using chest X-ray (CXR) with computer-aided detection powered by deep learning-based artificial intelligence (AI-CAD) provided this opportunity. …”
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Optimization of Multi-Source Remote Sensing Soil Salinity Estimation Based on Different Salinization Degrees by Huifang Chen, Jingwei Wu, Chi Xu

“…Subsequently, machine learning methods such as random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR) were employed, in combination with sensitive spectral indices, to develop a multi-source remote sensing soil salinity estimation model optimized for different salinization degrees (mild or lower salinization vs. moderate or higher salinization). …”
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Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features by Hongwei Zhang, Kexin Wang, Shurong Liu, Guowei Chen, Yong Jiang, Yingchao Wu, Xiaocong Pang, Xiaoying Wang, Junling Zhang, Xin Wang

“…This study aimed to develop a machine learning model for predicting metastasis in No. 253 LN. …”
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Identifying cardiovascular disease risk in the U.S. population using environmental volatile organic compounds exposure: A machine learning predictive model based on the SHAP method... by Qingan Fu, Yanze Wu, Min Zhu, Yunlei Xia, Qingyun Yu, Zhekang Liu, Xiaowei Ma, Renqiang Yang

“…This study aims to develop a machine learning (ML) model to predict CVD risk based on VOC exposure and demographic data using SHapley Additive exPlanations (SHAP) for interpretability. …”
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Novel Snapshot-Based Hyperspectral Conversion for Dermatological Lesion Detection via YOLO Object Detection Models by Nan-Chieh Huang, Arvind Mukundan, Riya Karmakar, Syna Syna, Wen-Yen Chang, Hsiang-Chen Wang

“…These findings indicate that integrating snapshot-based narrowband imaging with deep learning object detection models can improve early diagnosis and has potential applications in broader clinical contexts.…”
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Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study by Yuanxi Luo, Yuanxi Luo, Zhiyang Yin, Xin Li, Xin Li, Chong Sheng, Ping Zhang, Dongjin Wang, Dongjin Wang, Yunxing Xue

“…For nomogram construction, we utilized an ensemble machine learning framework, combining Boruta algorithm-based feature selection with Random Forest (RF) and XGBoost analyses to determine key predictive parameters.ResultsThroughout the median follow-up duration of 84 months, we documented 1,500 incident CVD cases, comprising 1,148 cardiac events and 488 cerebrovascular events. …”
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Neural models in diagnostics of the financial result of housing and utility enterprises by I. P. Kurochkina, I. I. Kalinin, L. A. Mamatova, E. B. Shuvalova

“…The  proposed universal  model  is presented  in the article in relation  to the  company’s  characteristics  in the  housing and  utilities  sector.The  article  proposes a  method  for  diagnosing  the  level  of  the housing and  utility  company’s  financial  condition  based on the use of a factor neural model of the financial results of their activities.Materials and methods.  …”
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Machine-Learning-Based Integrated Mining Big Data and Multi-Dimensional Ore-Forming Prediction: A Case Study of Yanshan Iron Mine, Hebei, China by Yuhao Chen, Gongwen Wang, Nini Mou, Leilei Huang, Rong Mei, Mingyuan Zhang

“…Combined with LiDAR image elevation data, a real-time three-dimensional surface mineral monitoring model for the mining area was built. (4) The Bagged Positive Label Unlabeled Learning (BPUL) method was adopted to integrate five evidence maps—carbonate alteration, chloritization, mixed rockization, fault zones, and magnetic anomalies—to conduct three-dimensional mineralization prediction analysis for the mining area. …”
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Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation by Muhammad Ahmad, Ildar Batyrshin, Grigori Sidorov

“…By analyzing this sentiment, we used 4 state-of-the-art machine learning models, 2 deep learning models, 3 transformer models, and 1 large language model (GPT-3.5 Turbo) to predict overdose risks to improve health care response and intervention strategies. …”
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Rapid differentiation of patients with lung cancers from benign lung nodule based on dried serum Fourier-transform infrared spectroscopy combined with machine learning algorithms by Huanyu Li, Lixue Dai, Shaomei Guo, Hongluan Wang, Lei Lei, Jie Yu, Xiaoyun Li, Jun Wang

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Teachers' perceptions, attitudes, and acceptance of artificial intelligence (AI) educational learning tools: An exploratory study on AI literacy for young students by Iris Heung Yue Yim, Rupert Wegerif

“…The study reveals that teachers have positive perceptions regarding the usefulness and ease of use of AI educational learning tools in their AI literacy teaching. …”
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Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data by Nikolaos Bakalos, Nikolaos Papadakis, Antonios Litke

“…The captured posts were then analyzed using a sentiment analysis framework, developed using state-of-the-art deep machine learning (ML) models. This framework provides labeling for the captured posts based on their content (i.e., classifies them as positive or negative opinions). …”
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Computer Vision-Based Lane Detection and Detection of Vehicle, Traffic Sign, Pedestrian Using YOLOv5 by Raşit Köker, Osman Eldoğan, Gülyeter Öztürk

“…In our proposed system, road images are captured using a camera positioned behind the front windshield of the vehicle. …”
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