Explainable Artificial Intelligence Driven Segmentation for Cervical Cancer Screening by Niruthikka Sritharan, Nishaanthini Gnanavel, Prathushan Inparaj, Dulani Meedeniya, Pratheepan Yogarajah

“…Early and accurate identification of abnormal cervical cells is crucial for effective treatment and improved survival rates. This paper addresses the development of a novel weakly supervised segmentation framework that combines binary classification, Explainable Artificial Intelligence (XAI) techniques, and GraphCut to automate cervical cancer screening. …”
Get full text

End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

“…Both conventional machine learning algorithms and deep convolutional neural networks (DCNN) were employed to develop discriminative models using independent datasets. …”
Get full text

Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

“…Compared to standard U-Net, the proposed model achieves more than a 29% increase in F1-score and a 62% improvement in Intersection over Union (IoU) while reducing segmentation loss by 71%. …”
Get full text

Integration of Bulk and Single-Cell Transcriptomics Reveals BCL2L14 as a Novel IGKC+ T Cell-Associated Therapeutic Target in Breast Cancer by He J, Akhtar A, Li J, Wei Q, Yuan Y, Ran J, Ma Y, Chen D

“…To pinpoint key regulatory genes, we applied machine learning algorithms. Based on the hub genes identified, we constructed a prognostic risk model and developed a nomogram to aid clinical decision-making. …”
Get full text

Plausible Vehicle Trajectory Augmentation With Hybrid Machine Learning by Junyeop Park, Hyeonsoo Jang, Byeongju Kang, Yunhyoung Hwang

“…Validation on the inD dataset confirms that our approach excels in expanding training datasets, yielding substantial improvements in trajectory prediction accuracy for autonomous vehicles when applied to a vanilla long short-term memory model. …”
Get full text

Artificial Intelligence: The Strategy of Financial Risk Management by A. Kumar, A Kumar, S. Kumari, S. Kumar, N. Kumari, A. K. Behura

“…The paper presents the most promising AI technologies and techniques such as RPA, Data Management, Blockchain, MRL, MRC, CRU, Deep Learning, OML, Modelling and Stress Testing, Machine Learning and Algorithms, Neural Networks, Decision Trees, CPM, CRA, Black Box, etc. to improve “Financial Risk Management (FRM)”.…”
Get full text

Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation by Liang Liu, Xige Zhang, Jiahui Zhou, Kai Niu, Zixuan Guo, Yawen Zhao, Meng Zhang

“…As maximum power point tracking (MPPT) algorithms have developed towards multi-task intelligent computing, processors in photovoltaic power generation control systems must be capable of achieving a higher performance. …”
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

“…We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no 'best' preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. Further, we developed novel signatures for each preprocessing method and the risk classifications from each were incorporated in a meta-random forest model. …”
Get full text

A Two-Stage Corrosion Defect Detection Method for Substation Equipment Based on Object Detection and Semantic Segmentation by Zhigao Wang, Xinsheng Lan, Yong Zhou, Fangqiang Wang, Mei Wang, Yang Chen, Guoliang Zhou, Qing Hu

“…Experimental results indicate that the improved YOLOv8 and DDRNet, incorporating the multi-head attention block, boost the mAP and mIoU by 5.8 and 9.7, respectively, when compared to the original method on our self-built dataset. …”
Get full text

Elevated Temperature Effects on FRP–Concrete Bond Behavior: A Comprehensive Review and Machine Learning-Based Bond Strength Prediction by Aseel Salameh, Rami Hawileh, Hussam Safieh, Maha Assad, Jamal Abdalla

“…Because of their improved properties, FRP composites are vastly used in the strengthening of aged concrete infrastructures. …”
Get full text

Emotion Detection and Student Engagement in Distance Learning During Containment Due to the COVID-19 by Benyoussef Abdellaoui, Ahmed Remaida, Zineb Sabri, Younes EL BOUZEKRI EL IDRISSI, Aniss Moumen

“…A private dataset has been created to train and evaluate the model. The results show that it is possible to measure participation, learn about feelings, and use them to make decisions in favor of student outcomes and improve teaching and learning methods. …”
Get full text

Comparison of clinical nasal endoscopy, optical biopsy, and artificial intelligence in early diagnosis and treatment planning in laryngeal cancer: a prospective observational study by Ruifang Hu, Xianping Liu, Yong Zhang, Clement Arthur, Dongguang Qin

“…Prompt diagnosis is crucial to improving survival and function. Direct laryngoscopy and imaging modalities are conventional diagnostic methods. …”
Get full text

An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

“…To address these challenges, this study proposes a completely new gridded precipitation generation scheme that integrates long-term daily observations from 3746 gauges with 11 key precipitation-related covariates. Building upon the improved inverse distance weighting interpolation method used in our previous dataset CHM_PRE V1, we integrated a machine learning algorithm – light gradient boosting machine (LGBM) – to incorporate precipitation-related covariates in a data-driven manner. …”
Get full text

Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…This optimization of the signal enhancement methodology significantly improved the fault diagnosis accuracy. As per the result obtained, Random Forest method consistently outperforms when applied to the feature-enhanced SNR dataset. …”
Get full text

White Blood Cell Detection Based on FBDM-YOLOv8s by Borui Sun, Xiangsuo Fan, Jie Meng, Jinfeng Wang, Huajin Chen, Lei Liu

“…This article proposes a white blood cell detection method based on an improved YOLOv8s to enhance the accurate detection of different categories of normal white blood cells. …”
Get full text

Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer by Hao Yu, Quan Yuan, Liu-Xing Feng, Jia-Huan Xu, Shen-Yuan Zhan, Zhi-min Li, Shuang-Jia Wang

“…These results offer valuable insights into PC progression, providing a foundation for improved clinical management and future research.…”
Get full text

Anatomical Parameter-driven Volumetric Modulated Arc Therapy Optimization in Left-sided Breast Cancer: A Machine Learning Framework for Lung Dose Prediction by Mukesh Kumar Zope, Deepali Patil, Rishi Raj, Seema Devi, Richa Madhawi

“…In addition, we established predictive models for lung doses utilizing the Least Absolute Shrinkage and Selection Operator, ridge, and linear regression algorithms while also evaluating dosimetric parameters for both the PTV and the organs at risk (OARs). …”
Get full text

Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem. by Wesley D Swingley, D'Arcy R Meyer-Dombard, Everett L Shock, Eric B Alsop, Heinz D Falenski, Jeff R Havig, Jason Raymond

“…Microbial life at BP transitions from a 92 °C chemotrophic streamer biofilm community in the BP source pool to a 56 °C phototrophic mat community. We improved automated annotation of the BP environmental genomes using BLAST-based Markov clustering. …”
Get full text

Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…Classifying all domain 22 significant features using a random forest model improved classification accuracy to 84.9%. …”
Get full text

Identification of novel gut microbiota-related biomarkers in cerebral hemorrhagic stroke by Fengli Ye, Huili Li, Hongying Li, Xiue Mu

“…Hub genes were screened using LASSO, RandomForest, and SVM-RFE algorithms. Validation was conducted in plasma samples from ICH patients (n=20) and controls (n < 20) by qRT-PCR, and in a collagenase-induced ICH mouse model. …”
Get full text