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

“…A clinical-radiological model (CR model) was constructed, and two fusion models were generated by combining the radiomics or/and CR models using a stacking algorithm (fusion_R and fusion_CR). Model performance was evaluated using AUC, accuracy, sensitivity, and specificity.ResultsThe MDelta model demonstrated higher sensitivity compared to the MCVT-AP and MCVT-PVP models. …”
Get full text

Directed disruption of IL2 aggregation and receptor binding sites produces designer biologics with enhanced specificity and improved production capacity by Amy Dashwood, Ntombizodwa Makuyana, Rob van der Kant, Arman Ghodsinia, Alvaro R. Hernandez, Stephanie Lienart, Oliver Burton, James Dooley, Magda Ali, Lubna Kouser, Francisco Naranjo, Matthew G. Holt, Frederic Rousseau, Joost Schymkowitz, Adrian Liston

“…Here we use SolubiS and dTANGO, computational algorithm-based methods, to predict mutations within the IL2 structure to improve protein production yield in muteins with altered cellular selectivity, to generate combined muteins with elevated therapeutic potential. …”
Get full text

ML-based top taggers: Performance, uncertainty and impact of tower & tracker data integration by Rameswar Sahu, Kirtiman Ghosh

“…Machine learning algorithms have the capacity to discern intricate features directly from raw data. …”
Get full text

Trajectory Aware Deep Reinforcement Learning Navigation Using Multichannel Cost Maps by Tareq A. Fahmy, Omar M. Shehata, Shady A. Maged

“…Additionally, navigation efficiency improved by 35% in tunnel scenarios and by 12% in dense-environment navigation compared to standard methods that rely on raw sensor data or frame stacking.…”
Get full text

Rhodanine derivatives as potent anti-HIV and anti-HSV microbicides. by Cristina Tintori, Giulia Iovenitti, Elisa Rita Ceresola, Roberto Ferrarese, Claudio Zamperini, Annalaura Brai, Giulio Poli, Elena Dreassi, Valeria Cagno, David Lembo, Filippo Canducci, Maurizio Botta

Get full text

Aircraft Sensor Fault Diagnosis Based on GraphSage and Attention Mechanism by Zhongzhi Li, Jinyi Ma, Rong Fan, Yunmei Zhao, Jianliang Ai, Yiqun Dong

“…First, signal data representing the coupling characteristics of various sensors are constructed through data stacking. These signals are then transformed into graph data with a specific topology reflecting the overall sensor status of the aircraft using K-nearest neighbor and Radius classification algorithms. …”
Get full text

Assessing Physiological Stress Responses in Student Nurses Using Mixed Reality Training by Kamelia Sepanloo, Daniel Shevelev, Young-Jun Son, Shravan Aras, Janine E. Hinton

“…Among the models tested, the Stacking Classifier demonstrated the highest classification accuracy of 96.4%, outperforming both Random Forest (96.18%) and Gradient Boosting (95.35%). …”
Get full text

A Soft-Fault Diagnosis Method for Coastal Lightning Location Networks Based on Observer Pattern by Yiming Zhang, Ping Guo

“…This paper first analyzes the main factors contributing to the error of the lightning location algorithm under this mode, proposes an observer pattern estimation algorithm (OPE) for lightning location, and defines the proportion of improvement in lightning positioning accuracy (PI) caused by the OPE algorithm. …”
Get full text

An explainable AI-based approach for predicting undergraduate students academic performance by Fatema Tuz Johora, Md Nahid Hasan, Aditya Rajbongshi, Md Ashrafuzzaman, Farzana Akter

“…SMOTE (Synthetic Minority Oversampling Technique) and normalizing algorithms were employed to attain data balance and feature scaling, respectively. …”
Get full text

Enhancing Speed and Imperceptibility in Watermarking Systems by Leveraging Galois Field Tables by Yasmin Alaa Hassan, Abdul Monem S. Rahma

“…Watermarking research still faces difficulties in striking a balance between speed, robustness, and imperceptibility. …”
Get full text

Computer-Aided Facial Soft Tissue Reconstruction with Computer Vision: A Modern Approach to Identifying Unknown Individuals by Svenja Preuß, Sven Becker, Jasmin Rosenfelder, Dirk Labudde

“…The models did not indicate significant similarity, highlighting a gap between human perception and algorithmic assessment. These findings suggest that current face recognition algorithms may not yet be fully suited to evaluating reconstructions, which tend to deviate in subtle but critical facial features. …”
Get full text

Early prediction of cognitive impairment in adults aged 20 years and older using machine learning and biomarkers of heavy metal exposure by Ali Nabavi, Farimah Safari, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Hossein Molavi Vardanjani

“…Variables included demographics, medical history, lifestyle factors, and blood and urine levels of lead, cadmium, manganese, and other metals. Machine learning algorithms were trained on 90 % of data and evaluated on 10 %. …”
Get full text

Machine Learning Approaches for Real-Time Mineral Classification and Educational Applications by Paraskevas Tsangaratos, Ioanna Ilia, Nikolaos Spanoudakis, Georgios Karageorgiou, Maria Perraki

“…The main objective of the present study was to develop a real-time mineral classification system designed for multiple detection, which integrates classical computer vision techniques with advanced deep learning algorithms. The system employs three CNN architectures—VGG-16, Xception, and MobileNet V2—designed to identify multiple minerals within a single frame and output probabilities for various mineral types, including Pyrite, Aragonite, Quartz, Obsidian, Gypsum, Azurite, and Hematite. …”
Get full text

Development and validation of machine learning models for osteoporosis prediction in chronic kidney disease patients: Data from National Health and Nutrition Examination survey by Hui Li, Ya Zhang, Chong Zhang

“…Additionally, stacking ensemble models were constructed. Model performance was evaluated using receiver operating characteristic curves, F1 scores, Matthews correlation coefficient, and Brier scores. …”
Get full text

HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors by Viet-Khoa Tran-Nguyen, Ulrick Fineddie Randriharimanamizara, Olivier Taboureau

“…Multiple structure-based artificial intelligence (AI) binary classifiers for predicting hERG inhibitors were developed, employing, as descriptors, protein–ligand extended connectivity (PLEC) fingerprints fed into random forest, extreme gradient boosting, and deep neural network (DNN) algorithms. Our best-performing model, a stacking ensemble classifier with a DNN meta-learner, achieved state-of-the-art classification performance, accurately identifying 86% of molecules having half-maximal inhibitory concentrations (IC50s) not exceeding 20 µM in our challenging test set, including 94% of hERG blockers whose IC50s were not greater than 1 µM. …”
Get full text

Enhancing Border Learning for Better Image Denoising by Xin Ge, Yu Zhu, Liping Qi, Yaoqi Hu, Jinqiu Sun, Yanning Zhang

“…Inspired by this observation, patch-wise denoising algorithms were explored to derive a CNN architecture that avoids border effects. …”
Get full text

Deep Learning Model-Based Detection of Anemia from Conjunctiva Images by Najmus Sehar, Nirmala Krishnamoorthi, C. Vinoth Kumar

“…These processed and augmented images were then utilized to train and test multiple models, including statistical regression, machine learning algorithms, and deep learning frameworks. Results The stacking ensemble framework, which includes the models VGG16, ResNet-50, and InceptionV3, achieved a high area under the curve score of 0.97. …”
Get full text

Machine Learning‐Enabled Drug‐Induced Toxicity Prediction by Changsen Bai, Lianlian Wu, Ruijiang Li, Yang Cao, Song He, Xiaochen Bo

“…In this review, 10 categories of drug‐induced toxicity is examined, summarizing the characteristics and applicable ML models, including both predictive and interpretable algorithms, striking a balance between breadth and depth. …”
Get full text

Reservoir Computing-Based Digital Self-Interference Cancellation for In-Band Full-Duplex Radios by Zhikai Liu, Haifeng Luo, Tharmalingam Ratnarajah

“…Our results reveal that the RC-DSIC scheme attains 99.84% of the performance offered by PL-based DSIC algorithms while requiring only 1.51% of the computational demand. …”
Get full text

Prediction of early breast cancer patient survival using ensembles of hypoxia signatures. by Inna Y Gong, Natalie S Fox, Vincent Huang, Paul C Boutros

“…Interestingly, the classification of these biomarkers and its ensemble show striking consistency, demonstrating that similar intrinsic biological information are being faithfully represented. …”
Get full text