Detection of Undiagnosed Liver Cirrhosis via Artificial Intelligence-Enabled Electrocardiogram (DULCE): Rationale and design of a pragmatic cluster randomized clinical trial by Amy Olofson, Ryan Lennon, Blake Kassmeyer, Kan Liu, Zacchi I. Attia, David Rushlow, Puru Rattan, Joseph C. Ahn, Paul A. Friedman, Alina Allen, Patrick S. Kamath, Vijay H. Shah, Peter A. Noseworthy, Douglas A. Simonetto

“…The primary endpoint will be detection of advanced CLD (defined as stage 3–4 on blood- or imaging-based noninvasive liver disease assessment or liver biopsy). …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Unsupervised learning (Louvain clustering) was used to identify distinct movement patterns, whereas supervised learning algorithms were employed to classify EOA status. …”
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Comparative Study of Cell Nuclei Segmentation Based on Computational and Handcrafted Features Using Machine Learning Algorithms by Rashadul Islam Sumon, Md Ariful Islam Mozumdar, Salma Akter, Shah Muhammad Imtiyaj Uddin, Mohammad Hassan Ali Al-Onaizan, Reem Ibrahim Alkanhel, Mohammed Saleh Ali Muthanna

“…<b>Methods:</b> This work explores machine learning approaches for nuclei segmentation by evaluating the quality of nuclei image segmentation. We employed several methods, including K-means clustering, Random Forest (RF), Support Vector Machine (SVM) with handcrafted features, and Logistic Regression (LR) using features derived from Convolutional Neural Networks (CNNs). …”
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Comparative Analysis of Machine Learning Algorithms and Statistical Techniques for Data Analysis in Crop Growth Monitoring with NDVI by M. Arunachalam, S. Sekar, A. M. Erdmann, V. V. Sajith Variyar, R. Sivanpillai

“…Initially we clustered the pixels in these images for each field using AP and determine the number of clusters. …”
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First Joint MUSE, Hubble Space Telescope, and JWST Spectrophotometric Analysis of the Intracluster Light: The Case of the Relaxed Cluster RX J2129.7+0005 by Yolanda Jiménez-Teja, Antonio Gimenez-Alcazar, Renato A. Dupke, Patrick Prado-Santos, Jose M. Viĺchez, Nícolas O. L. de Oliveira, Paola Dimauro, Anton M. Koekemoer, Patrick Kelly, Jens Hjorth, Wenlei Chen

“…Using 15 broadband, deep images observed with the Hubble Space Telescope and JWST in the optical and the infrared, plus deep integral field spectroscopy from MUSE, we computed a total of 3696 ICL maps spanning the spectral range ∼0.4−5 μ m with our algorithm CICLE, a method that is extremely well suited to analyzing large samples of data in a fully automated way. …”
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Precision in 3D: A Fast and Accurate Algorithm for Reproducible Motoneuron Structure and Protein Expression Analysis by Morgan Highlander, Shelby Ward, Bradley LeHoty, Teresa Garrett, Sherif Elbasiouny

“…With no manual tracing, the algorithm produces 3D Cartesian reconstructions of motoneuron somas from 60× IHC images of mouse lumbar spinal tissue. …”
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An assessment of the long-term change of the Mersin west coastline using digital shoreline analysis system and detection of pattern similarity using fuzzy C-means clustering by Ozcan Zorlu, Lutfiye Kusak

“…The Canny edge detection algorithm was employed to delineate shorelines from the classified images. …”
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Quantitative Comparison of Geographical Color of Traditional Village Architectural Heritage Based on K-Means Color Clustering—A Case Study of Southeastern Hubei Province, China by Li Dong, Meiqi Kang

“…However, under the wave of contemporary rapid economic development, the color of traditional village architectural heritage is facing serious challenges. The K-means clustering algorithm has outstanding advantages in image color clustering and is suitable for the large-scale data collection of sample picture primary colors to reduce subjective bias and can be combined with the HSV color space to optimize the results. …”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…Recent systems take advantage of the synergy between machine learning, data mining, and image processing to extract/analyze features from crowded zones and recognize patterns and anomalies from the crowd behavior. …”
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Accurate Paddy Rice Mapping Based on Phenology-Based Features and Object-Based Classification by Jiayi Zhang, Lixin Gao, Miao Liu, Yingying Dong, Chongwen Liu, Raffaele Casa, Stefano Pignatti, Wenjiang Huang, Zhenhai Li, Tingting Tian, Richa Hu

“…In this study, the rice backscattering intensity difference index from the vertically polarized backscatter intensity of Sentinel-1 and the phenology differential index from the spectral indices of two critical rice phenological phases of Sentinel-2 images were constructed. Other spectral features, including spectral indices, tasseled cap, and texture features, were computed using simple non-iterative clustering (SNIC) to achieve image segmentation. …”
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Analytical approach to digital channel performance optimization of mobile money transactions in emerging markets by Adeolu Dairo, Krisztián Szűcs

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FECI-RTDETR a Lightweight Unmanned Aerial Vehicle Infrared Small Target Detector Algorithm Based on RT-DETR by Renzheng Xue, Shijie Hua, Haiqiang Xu

“…Addressing the challenges of small target detection in aerial infrared images from a drone&#x2019;s perspective, such as diverse target scales, complex backgrounds, the clustering of small targets, and limited computational resources of the drone platform. …”
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A Novel Laboratory Technique for Measuring Grain‐Size‐Specific Transport Characteristics of Bed Load Pulses by Kevin Reiterer, Thomas Gold, Christoph Hauer, Helmut Habersack, Christine Sindelar

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Research on multi-algorithm and explainable AI techniques for predictive modeling of acute spinal cord injury using multimodal data by Jiaojiao Tai, Linbang Wang, Yijun Xie, Yang Li, Hua Fu, Xiaowen Ma, Haiyan Li, Xinying Li, Ziqiang Yan, Jingkun Liu

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Trajectories of Cognitive Complaints in Patients With Breast Cancer and Their Association With Psychosocial and Neurobiological Factors by Rob Colaes, Gwen Schroyen, Rebeca Alejandra Gavrila Laic, Jeroen Blommaert, Sigrid Hatse, Ann Smeets, Stefan Sunaert, Sabine Deprez

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iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction by Bicheng Ye, Jun Fan, Lei Xue, Yu Zhuang, Peng Luo, Aimin Jiang, Jiaheng Xie, Qifan Li, Xiaoqing Liang, Jiaxiong Tan, Songyun Zhao, Wenhang Zhou, Chuanli Ren, Haoran Lin, Pengpeng Zhang

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A Lightweight Model for Shine Muscat Grape Detection in Complex Environments Based on the YOLOv8 Architecture by Changlei Tian, Zhanchong Liu, Haosen Chen, Fanglong Dong, Xiaoxiang Liu, Cong Lin

“…Evaluated on the newly developed Shine-Muscat-Complex dataset of 4715 images, the proposed model achieved a 2.6% improvement in mean Average Precision (mAP) over YOLOv8n while reducing parameters by 36.8%, FLOPs by 34.1%, and inference time by 15%. …”
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Efficient early-stage disease detection in pomegranate (Punica granatum) using convolutional neural networks optimized by honey badger optimization algorithm by Sameera P, Abhay A. Deshpande

“…Pre-processed image was segmented using k-means clustering. The features for early-stage disease detection are color-based, region-based and texture-based. …”
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An Improved Random Forest Approach on GAN-Based Dataset Augmentation for Fog Observation by Yucan Cao, Panpan Zhao, Balin Xu, Jingshu Liang

“…Key image features related to fog are extracted, and an RF method, integrated with the hierarchical and k-medoid clustering, is deployed to estimate the fog density. …”
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study by Inge A. H. van den Berk, Colin Jacobs, Maadrika M. N. P. Kanglie, Onno M. Mets, Miranda Snoeren, Alexander D. Montauban van Swijndregt, Elisabeth M. Taal, Tjitske S. R. van Engelen, Jan M. Prins, Shandra Bipat, Patrick M. M. Bossuyt, Jaap Stoker, The OPTIMACT study group

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