Multi-model machine learning framework for lung cancer risk prediction: A comparative analysis of nine classifiers with hybrid and ensemble approaches using behavioral and hematolo... by Vinod Kumar, Chander prabha, Deepali Gupta, Sapna Juneja, Swati Kumari, Ali Nauman

“…A multi-model machine learning approach compares nine algorithms: KNN, AdaBoost (AB), logistic regression (LR), random forest (RF), SVM, naive Bayes (NB), decision tree (DT), gradient boosting (GB), and stochastic gradient descent (SGD). …”
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Predicting the occurrence of probable sarcopenia in middle-aged and elderly patients with coronary artery disease: development and validation of a clinical model by Xiaolan Sun, Jia Xu, Feier Chen, Haiyan Lei, Wei Chen, Fang Ding, Xueping Li

“…Abstract The objective of this research was to identify the factors contributing to the decline in handgrip strength among middle-aged and elderly individuals with this condition. In addition, an algorithmic model for the detection of probable sarcopenia will be developed. …”
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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning by Brianna J. Pickstone, Hugh A. Graham, Andrew M. Cunliffe

“…This study aims to compare the performance of three machine learning algorithms (Multiple Linear Regression (MLR), Random Forest (RF), and Convolutional Neural Networks (CNN)) when using PlanetScope and Sentinel-2 imagery to improve the accuracy of height predictions. …”
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SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…Smoke and fire detection is vital for timely fire alarms, but traditional sensor-based methods are often unresponsive and costly. …”
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An Attention-based Model for Recognition of Facial Expressions Using CNN-BiLSTM by Sushil Kumar Singh, Manish Kumar, Ikram Majeed Khan, A. Jayanthiladevi, Chirag Agarwal

“…Traditional deep learning algorithms have faced significant challenges when processing images with occlusion, uneven lighting, and positional inconsistencies and addressing dataset imbalances. …”
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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…Accurate on-orbit perception of such targets, particularly those without cooperative markers, requires advanced algorithms and efficient system architectures. This study presents a hardware–software co-design framework for the pose estimation of non-cooperative targets. …”
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A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

“…This study proposes a novel technique utilizing ML and DL algorithms for threat detection. We began with data preprocessing, which included cleansing the data, addressing missing values through Multiple Imputation by Chained Equations (MICE), and applying transformations such as encoding and standard scaling. …”
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Challenges and opportunities for precision livestock farming applications in the rabbit production sector by Tomás Norton, María Cambra-López

“…When considering the future impact of PLF, early disease detection probably offers the highest potential for rabbit production. …”
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Machine Learning-Driven Prediction of Brain Age for Alzheimer’s Risk: APOE4 Genotype and Gender Effects by Carter Woods, Xin Xing, Subash Khanal, Ai-Ling Lin

“…This study aimed to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the effects of the APOE4 genotype and gender. …”
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Weighted Content Similarity Feature for Software Architecture Anti-Patterns Prediction by Somayeh Kalhor, Mohammad Reza Keyvanpour

“…So, it is more effective than these two features in predicting dependencies between components using machine learning algorithms.…”
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Dengue Contingency Planning: From Research to Policy and Practice. by Silvia Runge-Ranzinger, Axel Kroeger, Piero Olliaro, Philip J McCall, Gustavo Sánchez Tejeda, Linda S Lloyd, Lokman Hakim, Leigh R Bowman, Olaf Horstick, Giovanini Coelho

“…The Technical Handbook for Surveillance, Dengue Outbreak Prediction/ Detection and Outbreak Response seeks to provide countries with evidence-based best practices to justify the declaration of an outbreak and the mobilization of the resources required to implement an effective dengue contingency plan.…”
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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. …”
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Comparison of ileus risk in selected second-generation antipsychotics based on FAERS database by Yaqian Tan, Hui Xia, Qi Song

“…In disproportionality analysis, the algorithms of reporting odds ratio (ROR) and information component (IC) were applied for ileus risk signal detection. …”
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Movement Disorders and Smart Wrist Devices: A Comprehensive Study by Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

“…Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. …”
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Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques by Mohammed Qader Kheder, Aree Ali Mohammed

“…The data, which is collected by sensors and cameras, is processed using various image processing algorithms and it is sent to the cloud to be available for drivers and commuters through a mobile application. …”
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The invariance of current energy fourier spectrum of discrete real signals on finite intervals by V. A. Ponomarev, O. V. Ponomareva

“…The paper deals with the problems of measuring Fourier spectrum of signals in the base of discrete exponential functions. Methods and algorithms of sliding measurements of energy Fourier spectrum of signals on finite intervals were described. …”
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Fostering non-intrusive load monitoring for smart energy management in industrial applications: an active machine learning approach by Lukas Fabri, Daniel Leuthe, Lars-Manuel Schneider, Simon Wenninger

“…We compare three disaggregation algorithms with a benchmark model by efficiently selecting a subset of training data through three query strategies that identify the data requiring labeling. …”
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ENDOCRINE PANCREATIC FUNCTION IN ACUTE PANCREATITIS by P. V. Novokhatny

“…This finding was not detected only in patients after severe acute pancreatitis. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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An Improved Tree Crown Delineation Method Based on a Gradient Feature-Driven Expansion Process Using Airborne LiDAR Data by Jiaxuan Jia, Lei Zhang, Kai Yin, Uwe Sörgel

“…Currently, raster data such as the canopy height model derived from airborne light detection and ranging (LiDAR) data have been widely used in large-scale ITCD. …”
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