Improving appendix cancer prediction with SHAP-based feature engineering for machine learning models: a prediction study by Ji Yoon Kim

“…Purpose This study aimed to leverage Shapley additive explanation (SHAP)-based feature engineering to predict appendix cancer. …”
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Psychomedical named entity recognition method based on multi-level feature extraction and multi-granularity embedding fusion by Zixuan Liu, Guofang Zhang, Yanguang Shen

“…The character embedding is pre-trained by MFE-BERT. And the BiLSTM model is utilized for the extraction of features at the character granularity. …”
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Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach by Utathya Aich, Arghyasree Saha, Marcin Woźniak, Muhammad Fazal Ijaz, Pawan Kumar Singh

“…In the third step, a newly developed Average subtraction wrapper-based feature selection method has been proposed to lower the number of irrelevant features. …”
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AHN-YOLO: A Lightweight Tomato Detection Method for Dense Small-Sized Features Based on YOLO Architecture by Wenhui Zhang, Feng Jiang

“…To effectively identify fine-grained disease features in complex scenarios while reducing deployment and training costs, this paper proposes a novel network architecture named AHN-YOLO, based on an improved YOLOv11-n framework that demonstrates balanced performance in multi-scale feature processing. …”
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Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics by Maochun Zhang, Qing Zhang, Xueying Wang, Xiaoli Peng, Jiao Chen, Hanfeng Yang

“…Prediction models were developed utilizing several ML algorithms by Python based on an integrated dataset of clinical features and ultrasound radiomics. …”
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Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features by Xinchun Xu, Xinchun Xu, Xinchun Xu, Yanhong Yan, Yanhong Yan, Yafeng Qu, Lianlian Zhang, Lianlian Zhang, Pinjing Hui, Pinjing Hui

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A Multisource Image Matching Method Based on Contrastive Network With Similarity Weighting by Zhen Han, Ning Lv, Tao Su, Yoong Choon Chang, Chen Chen

“…In this article, we propose an image matching method based on the contrastive network with similarity statistics weighting for MRS registration. …”
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IDDNet: Infrared Object Detection Network Based on Multi-Scale Fusion Dehazing by Shizun Sun, Shuo Han, Junwei Xu, Jie Zhao, Ziyu Xu, Lingjie Li, Zhaoming Han, Bo Mo

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Communication emitter individual identification based on 3D-Hibert energy spectrum and multi-scale fractal features by Jie HAN, Tao ZHANG, Huan-huan WANG, Dong-fang REN

“…For communication emitter identification,a novel method based on Hilbert-Huang transform (HHT) and multi-scale fractal features was proposed.First,the time frequency energy spectrum was derived via HHT,which was called a complicated curved surface in the three-dimension space,namely,3D-Hilbert energy spectrum.Then,the differential box dimension and the multi-fractal dimension was extracted to compose the feature vector under multi-scale segmentation using fractal theory.Finally,communication emitter individual identification was obtained using the two dimensions of features above and the support vector machine (SVM).Moreover,the novel method was compared with two existing methods to identify simulated and actual signals with different and the same modulation modes,respectively.Results show that the identification rate of the novel method is higher than that of the two other methods.The features extracted by the novel method have high stability,sufficiency,and identifiability,also outweigh the negative effects of the change of signal-to-noise ratio and the number of training samples and emitters.…”
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Automated Tomato Leaf Disease Detection Using Image Processing: An SVM-Based Approach with GLCM and SIFT Features by Rashid Khan, Nasir Ud Din, Asim Zaman, Bingding Huang

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Enhancing IDS for the IoMT based on advanced features selection and deep learning methods to increase the model trustworthiness. by Ahmed Muqdad Alnasrallah, Maheyzah Md Siraj, Hanan Ali Alrikabi

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Transformer Hierarchical Fault Diagnosis Model Based on Dissolved Gas Analysis of Insulating Oil and Class Overlap Features by Tie CHEN, Haowei LENG, Xianshan LI, Yifu CHEN

“…And then, a hierarchical fault diagnosis model is established based on the class overlap rate. The samples of each diagnosis layer are trained separately by the separate training method, and a two-class fuzzy support vector machine (FSVM) is constructed based on class overlap degrees to diagnose faults. …”
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Aspect-Level Sentiment Analysis Based on Position Features Using Multilevel Interactive Bidirectional GRU and Attention Mechanism by Xiaodi Wang, Xiaoliang Chen, Mingwei Tang, Tian Yang, Zhen Wang

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Prediction of Pilot Performance During Startle Events Based on Neuropsychophysiological Features of Stress Resilience and Cognitive Task Scores by Mate Gambiraza, Sinisa Popovic, Matej Kurtak, Tanja Jovanovic, Seth Norrholm, Kresimir Cosic

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Computer-aided diagnosis of hepatic cystic echinococcosis based on deep transfer learning features from ultrasound images by Miao Wu, Chuanbo Yan, Gan Sen

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A scoring model based on MRI features for predicting early recurrence after surgical resection of hepatocellular carcinoma by Yi-Jing Wang, Jian-Xia Xu, Tian-Yu Ke, Bao-Na Li, Xiao-Zhong Zheng, Jun-Yi Xiang, Shu-Feng Fan, Xiao-Shan Huang

“…ObjectivesBased on MRI features, a scoring model was constructed to predict early recurrence after surgical resection of hepatocellular carcinoma (HCC).MethodsA total of 310 patients from two centers with HCC (212 in the training cohort, 98 in the validation cohort) were collected from January 2017 to October 2023, all patients underwent preoperative MRI-enhanced examinations and were pathologically diagnosed after resection and were divided into early recurrence group and non-early recurrence group based on follow-up results. …”
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MRI-based intra-tumoral ecological diversity features and temporal characteristics for predicting microvascular invasion in hepatocellular carcinoma by Yuli Zeng, Huiqin Wu, Yanqiu Zhu, Chao Li, Dongyang Du, Yang Song, Sulian Su, Jie Qin, Guihua Jiang, Guihua Jiang, Guihua Jiang

“…The tumors were segmented into five distinct habitats using case-level clustering and a Gaussian mixture model was used to determine the optimal clusters based on the Bayesian information criterion to produce an iTED feature vector for each patient, which was used to assess intra-tumoral heterogeneity. …”
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Deep Learning Based Cross Domain Sentiment Classification for Urdu Language by Amna Altaf, Muhammad Waqas Anwar, Muhammad Hasan Jamal, Sana Hassan, Usama Ijaz Bajwa, Gyu Sang Choi, Imran Ashraf

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Dual-radiomics based on SHapley additive explanations for predicting hematologic toxicity in concurrent chemoradiotherapy patients by Luqiao Chen, Zhipeng He, Qianxi Ni, Qionghui Zhou, Xizi Long, Wenbin Yan, Qian Sui, Jiheng Liu

“…Patients were categorized by HT severity, with 80% of the data used for training and 20% for testing. Radiomic features and dosiomic features were extracted from the same regions of interest, and SHAP-based feature selection was employed. …”
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Research on laser point cloud classification based on Light-BotNet by Lei Genhua, Wang Lei, Zhang Zhiyong

“…The framework is to extract the features of point cloud data, construct the point cloud feature image with adjacent feature points as the input of the network framework, and finally take Light-BotNet as the network framework model for point cloud classification training. …”
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