Enhancing survival predictions in lung cancer with cystic airspaces: a multimodal approach combining clinical and radiomic features by Liang Yin, Jing Wang, Pingyou Fu, Lu Xing, Yuan Liu, Zongchang Li, Jie Gan

“…In the validation set, the area under the curve for the VDT model was 0.805, for the radiomic model 0.717, and for the fusion model 0.895, demonstrating the highest predictive performance (P < 0.05).ConclusionIntegrating VDT, radiomics, and clinical imaging features into a fusion model improves the accuracy of predicting the five-year survival rate for LCCA patients, enhancing personalized and precise cancer treatment.…”
Get full text

BIDpred: unraveling B cell Immunodominance hierarchical pattern using statistical feature discovery and deep learning prediction by Sungjin Choi, Dongsup Kim

“…Based on these findings, we developed BIDpred, a B cell ImmunoDominance predictor, that learns newly discovered features by leveraging protein language model embeddings and graph attention network to predict the immunodominance scores. …”
Get full text

Predicting immune status and gene mutations in stomach adenocarcinoma patients based on inflammatory response-related prognostic features by Huanjun Li, Jingtang Chen, Zhiliang Chen, Jingsheng Liao

“…Results We found that a high-inflammatory group was associated with poor prognosis in STAD patients. 14 inflammation-related DEGs out of 126 DEGs were identified to be associated with the prognosis of STAD patients, and the prognostic models and nomograms constructed from the subsequently identified key genes (SLC7A1, CD82, SERPINE1 ROS1 and SLC7A2) demonstrated a good predictive performance in terms of prognosis of STAD. …”
Get full text

CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals by Ugur Ince, Yunus Talu, Aleyna Duz, Suat Tas, Dahiru Tanko, Irem Tasci, Sengul Dogan, Abdul Hafeez Baig, Emrah Aydemir, Turker Tuncer

“…<b>Materials and Methods:</b> Two EEG datasets were collected to detect mental performance and stress. To achieve classification and explainable results, a new XFE model was developed, incorporating a novel feature extraction function called Cubic Pattern (CubicPat), which generates a three-dimensional feature vector by coding channels. …”
Get full text

Nomogram construction for overall survival in breast angiosarcoma based on clinicopathological features: a population-based cohort study by Peikai Ding, Luxiao Zhang, Shengbin Pei, Zheng Qu, Xiangyi Kong, Zhongzhao Wang, Jing Wang, Yi Fang

Get full text

A Lightweight Tri-Stream Feature Fusion Network for Speech Emotion Recognition by Ronghe Cao, Yunxing Wang, Xiaolong Wu, Shuang Jin, Huiling Niu

“…Existing approaches, focusing on prosodic features or deep representations from pre-trained models, often struggle to capture the full spectrum of emotional cues present in real-world speech. …”
Get full text

ECOLOGICAL RESILIENCE ASSESSMENT FEATURES OF NATURAL-INDUSTRIAL SYSTEMS BY INDEX-BASED METHODS USING SOFT COMPUTING by A.V. Masloboev

NBA Results Forecast: From League Dynamics Analysis to Predictive Model Implementation by Rodrigues F, Pires F

“…The methodology followed the CRISP-DM process, involving data preprocessing, feature selection, and model evaluation.…”
Get full text

ORF1ab codon frequency model predicts host-pathogen relationship in orthocoronavirinae by Phillip E. Davis, Joseph A. Russell

“…We show alternative examples for other viral coding sequences and feature representations that do not perform well and discuss what distinguishes the models that are performant. …”
Get full text

Robust and Lightweight Modeling of IoT Network Behaviors From Raw Traffic Packets by Aleksandar Pasquini, Rajesh Vasa, Irini Logothetis, Hassan Habibi Gharakheili, Alexander Chambers, Minh Tran

“…Recent studies show that neural network-based traffic analysis can achieve performance comparable to human feature-engineered ML pipelines. …”
Get full text

Improving Generalization of ML-Based IDS With Lifecycle-Based Dataset, Auto-Learning Features, and Deep Learning by Didik Sudyana, Ying-Dar Lin, Miel Verkerken, Ren-Hung Hwang, Yuan-Cheng Lai, Laurens D'Hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

“…The established model is tested on five public datasets to assess its generalization performance. …”
Get full text

Music source feature extraction based on improved attention mechanism and phase feature by Weina Yu

“…Results showed that this model was studied to perform well in music source separation experiments of vocals and accompaniment. …”
Get full text

Prediction of Metastasis in Paragangliomas and Pheochromocytomas Using Machine Learning Models: Explainability Challenges by Carmen García-Barceló, David Gil, David Tomás, David Bernabeu

“…Explainability techniques were integrated to provide insights into the key factors driving predictions. Additionally, a feature selection process was performed to identify the most influential variables and explore how their inclusion affects model performance. …”
Get full text

LCFANet: A Novel Lightweight Cross-Level Feature Aggregation Network for Small Agricultural Pest Detection by Shijian Huang, Yunong Tian, Yong Tan, Zize Liang

“…Extensive experiments on the public dataset demonstrate that the LCFANet-n model achieves a precision of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>71.7</mn><mo>%</mo></mrow></semantics></math></inline-formula>, recall of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>68.5</mn><mo>%</mo></mrow></semantics></math></inline-formula>, mAP50 of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>70.4</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and mAP50-95 of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>45.1</mn><mo>%</mo></mrow></semantics></math></inline-formula>, reaching state-of-the-art (SOTA) performance in small-sized pest detection while maintaining a lightweight architecture.…”
Get full text

A Joint Network of 3D-2D CNN Feature Hierarchy and Pyramidal Residual Model for Hyperspectral Image Classification by Hongwei Wei, Yufan Wang, Yu Sun, Jianfeng Zheng, Xiaodong Yu

“…However, the performance of many CNN models is constrained by the complexity of hyperspectral pictures. …”
Get full text

Confidence evaluation for feature selection in expanded feature space based on density of states by Koki Obinata, Yasuhiko Igarashi, Kenji Nagata, Keitaro Sodeyama, Masato Okada

“…This method allows us to compare the performance of the selected model to those of other models and evaluate its significance. …”
Get full text

Deep Learning-Based Speech Emotion Recognition Using Multi-Level Fusion of Concurrent Features by Samuel, Kakuba, Alwin, Poulose, Dong, Seog Han, Senior Member, Ieee

“…We also investigate the performance of multi-level feature fusion compared to single-level fusion using the multi-level transformer encoder model (MLTED) that we also propose in this paper. …”
Get full text

Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
Get full text

Recent Advancement in Small Traffic Sign Detection: Approaches and Dataset by R. Suresha, N. Manohar, G. Ajay Kumar, M. Rohit Singh

Get full text

Acoustic signatures of bulbar ALS: Predictive modeling with sustained vowels and LightGBM by Zahra Farrokhi, Seyed Amirali Zakavi, Arian Sarafraz, Maryam Valifard, Salar Yousefzadeh, Zahra Mashhadi Tafreshi, Omid Anbiyaee, Navid Rostami, Mahsa Asadi Anar, Niloofar Deravi

“…Model performance and feature importance were evaluated. …”
Get full text