Machine learning model for diagnosing salivary gland adenoid cystic carcinoma based on clinical and ultrasound features by Huan-Zhong Su, Zhi-Yong Li, Long-Cheng Hong, Yu-Hui Wu, Feng Zhang, Zuo-Bing Zhang, Xiao-Dong Zhang

“…Abstract Objective To develop and validate machine learning (ML) models for diagnosing salivary gland adenoid cystic carcinoma (ACC) in the salivary glands based on clinical and ultrasound features. Methods A total of 365 patients with ACC or non-ACC of the salivary glands treated at two centers were enrolled in training cohort, internal and external validation cohorts. …”
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ECG Signal Ｒecognition Based on Deep Stacked Network by ZHANG Ｒiu, WANG Ｒu, HUANG Jun, ZENG Xin

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Prediction of Remaining Life of Cutting Tool Based on DNN by LIU Sheng-hui, ZHANG Ren-jing, ZHANG Shu-li, MA Chao, ZHANG Hong-guo

“…In order to better solve the problem that the remaining life of cutting tool is difficult to predict accurately, this paper studies three aspects of the selection of monitoring indexes, the extraction of data features and the establishing of prediction models Firstly, Cutting force and vibration frequency were selected as the indirect monitoring indexes of cutting tool These two indexes can accurately reflect the state of cutting tool, and also can solve the problem that the selecting the direct monitoring indexes causes, the wear analysis results of cutting tool being too subjective in the traditional state monitoring method Secondly, feature extraction is carried out by using wavelet packet analysis, and then the entropy values of the monitoring data are obtained They are taken as the input data Thirdly, the input data are used as the training data and testing data of the prediction model based on Deep Neural Network (DNN) Finally, the simulation experiments of the prediction method are carried out by using the real data of the workshop The results show that the model can effectively predict the useful life…”
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Electrical impedance-based tissue classification for bladder tumor differentiation by Carina Veil, Franziska Krauß, Bastian Amend, Falko Fend, Oliver Sawodny

“…Based on the distance of the feature vector of a unknown measurement to a healthy reference, a Gaussian process classifier is trained. …”
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Pixel-Based Change Detection in Moving-Camera Videos Using Twin Convolutional Features on a Data-Constrained Scenario by Luiz G. C. Tavares, Allan F. Da Silva, Rafael Padilla, Lucas A. Thomaz, Sergio L. Netto, Eduardo A. B. Da Silva

“…To address these moving camera surveillance problems, the PBCD-MC method was developed based on a hybrid ensemble feature extractor, combining deep learning methods, responsible for generating high-level features, and tree-based algorithms, responsible for selecting and combining the deep features. …”
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Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning by Mehdi Rashidi, Serena Arima, Andrea Claudio Stetco, Chiara Coppola, Debora Musarò, Marco Greco, Marina Damato, Filomena My, Angela Lupo, Marta Lorenzo, Antonio Danieli, Giuseppe Maruccio, Alberto Argentiero, Andrea Buccoliero, Marcello Dorian Donzella, Michele Maffia

“…A dataset comprising 81 voice samples (41 from healthy individuals and 40 from PD patients) was utilized to train and evaluate common machine learning (ML) models using various types of features, including long-term (jitter, shimmer, and cepstral peak prominence (CPP)), short-term features (Mel-frequency cepstral coefficient (MFCC)), and non-standard measurements (pitch period entropy (PPE) and recurrence period density entropy (RPDE)). …”
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PLM-ATG: Identification of Autophagy Proteins by Integrating Protein Language Model Embeddings with PSSM-Based Features by Yangying Wang, Chunhua Wang

“…In this study, we propose PLM-ATG, a novel computational model that integrates support vector machines with the fusion of protein language model (PLM) embeddings and position-specific scoring matrix (PSSM)-based features for the ATG identification. First, we extracted sequence-based features and PSSM-based features as the inputs of six classifiers to establish baseline models. …”
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Hybrid face recognition under adverse conditions using appearance‐based and dynamic features of smile expression by Murat Taskiran, Nihan Kahraman, Cigdem Eroglu Erdem

“…Under such conditions, soft‐biometric features such as facial dynamics are expected to increase the performance if they are used together with appearance‐based features. …”
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Prediction of antipsychotic drug efficacy for schizophrenia treatment based on neural features of the resting-state functional connectome by Song Liu, Meng Wang, Weiyi Han, Anran Chen, Xuzhen Liu, Kang Liu, Xue Li, Yi Chen, Luwen Zhang, Qing Liu, Xiaoge Guo, Xiujuan Wang, Ning Kang, Yong Han, Yuanbo Li, Xi Su, Luxian Lv, Bing Liu, Wenqiang Li, Yongfeng Yang

“…This study discovered and validated a set of functional features based on resting-state connectome, where higher connectivity of positive features and lower connectivity of negative features at baseline were associated with a higher reduction rate of PANSS total score in patients and a better therapeutic effect. …”
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Prediction and validation of nanowire proteins in Oleidesulfovibrio alaskensis G20 using machine learning and feature engineering by Dheeraj Raya, Vincent Peta, Alain Bomgni, Shiva Aryal, Tuyen Duc Do, Kalimuthu Jawaharraj, David R. Salem, Venkataramana Gadhamshetty, Saurabh Sudha Dhiman, Etienne Z. Gnimpieba

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Small object detection in complex open-pit mine backgrounds based on improved YOLOv11 by ZHU Yongjun, CAI Guangqi, HAN Jin, MIAO Yanzi, MA Xiaoping, JIAO Wenhua

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Prediction of Attention Groups and Big Five Personality Traits from Gaze Features Collected from an Outlier Search Game by Rachid Rhyad Saboundji, Kinga Bettina Faragó, Violetta Firyaridi

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Classification and Recognition of Soybean Quality Based on Hyperspectral Imaging and Random Forest Methods by Man Chen, Zhichang Chang, Chengqian Jin, Gong Cheng, Shiguo Wang, Youliang Ni

“…Experimental results showed that the RF classification model based on SPA-BC preprocessed spectra and DE-tuned parameters achieved an optimal prediction accuracy of 1.0000 during training. …”
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A novel early stage drip irrigation system cost estimation model based on management and environmental variables by Masoud Pourgholam-Amiji, Khaled Ahmadaali, Abdolmajid Liaghat

“…The ANN model (MLP) was found to be the best model for a subset of features in the easily available feature part, with R2 = 0.912, RMSE = 0.008, and VE = 0.083 in the training stage and R2 = 0.882, RMSE = 0.009, and VE = 0.103 in the testing stage. …”
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Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical fe... by Dingxin Wang, Jianhao Qiu, Rongyang Li, Hui Tian

“…Lasso regression was utilized in order to identify key features, and a machine learning prediction model was constructed based on the screened key features. …”
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An Action Evaluation Method for Virtual Reality Simulation Power Training Based on an Improved Dynamic Time Warping Algorithm by Qingjie Xu, Yong Liu, Shuo Li

“…To address the shortcomings in action evaluation within VR simulation power training, this paper introduces a novel action recognition and evaluation method based on dynamic recognition of finger keypoints combined with an improved Dynamic Time Warping (DTW) algorithm. …”
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ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application by Rajib Kumar Halder, Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal, Sajeeb Saha, Rakib Hossen, Sabbir Ahmed, Mohammad Abu Tareq Rony, Mosammat Farida Akter

“…In this paper, we developed a machine learning-based kidney diseases prediction (ML‐CKDP) model with dual objectives: to enhance dataset preprocessing for CKD classification and to develop a web-based application for CKD prediction. …”
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Track Allocation Scheme for Ningbo City Railway Xiangshan Line Based on Express/Local Train Operation Mode by YAO Yanming, WANG Tao, ZONG Erkai, QI Tianyang

“…［Objective］ To support the important radial line development of the southern wing in Ningbo′s spatial framework featuring ′one core, one auxiliary and multiple centers′, the track allocation scheme for the Ningbo City Railway Xiangshan Line under express/local train operation mode is examined. …”
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Exploring Feature Selection with Deep Learning for Kidney Tissue Microarray Classification Using Infrared Spectral Imaging by Zachary Caterer, Jordan Langlois, Connor McKeown, Mikayla Hady, Samuel Stumo, Suman Setty, Michael Walsh, Rahul Gomes

“…Feature selection algorithms reduce data dimensionality, followed by a deep learning classification approach. …”
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Normalized Intrinsic Deep Features Based Zero-Watermarking Scheme for Remote Sensing Images Using U-Net and K-Means by Jie Zhang, Xu Xi, Jinglong Du, Xin He, Mingkang Wu, Yi Wei

“…During feature extraction, a specially trained U-Net network is employed to extract robust features for generalized recognition across multitype images. …”
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