Metabolomics of Papanicolaou Tests for the Discovery of Ovarian Cancer Biomarkers by Samyukta Sah, Elisabeth M. Schwiebert, Samuel G. Moore, Ying Liu, David A. Gaul, Kristin L. M. Boylan, Amy P. N. Skubitz, Facundo M. Fernández

“…Among these detected features, 453 unique lipids, representative of 20 different lipid subclasses, were annotated in all 29 samples. …”
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Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review by Jia-Mei Chen, Yan Li, Jun Xu, Lei Gong, Lin-Wei Wang, Wen-Lou Liu, Juan Liu

“…Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. …”
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Preoperative arterial and venous CT radiomics for survival prediction after pylorus preserving pancreatoduodenectomy in pancreatic head cancer by Annika Rastkhiz, Ali Rastkhiz, Felicia Erb, Maximilian Schulze-Hagen, Florian Tom Ulmer, Ulf Peter Neumann, Gregory van der Kroft, Christiane Katharina Kuhl, Daniel Truhn, Teresa Lemainque

“…No identifying information or images are included in this manuscript. Survival analysis revealed no significant differences when using arterial (p = 0.161) or venous (p = 0.668) phase features alone. …”
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Automating attendance management in human resources: A design science approach using computer vision and facial recognition by Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

“…It leverages Haar Cascade, enriched with carefully selected Haar features, such as Haar-like wavelets, and employs advanced edge detection techniques. …”
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A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan by Bingyue Dong, Weiyang Chen

“…Abstract In-depth exploration of the effects of genes on the development, physiology, and behavior of organisms requires high-precision phenotypic analysis. However, the overlap of body postures in group behavior and the similarity of movement patterns between strains pose challenges to accuracy analysis. …”
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Damage Identification Using Meta-Lens and Dual-Enhanced Backscattered Waves: Numerical and Experimental Design by Jiahui SHI, Gabriele Cazzulani, Claudio Sbarufatti

“… This paper introduces a Meta-lens designed for the detection of minute damage in Structural Health Monitoring (SHM) by amplifying backscattered waves originating from anomalous areas. …”
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Nonlinear Parameters for Monitoring Gear: Comparison Between Lempel-Ziv, Approximate Entropy, and Sample Entropy Complexity by Mourad Kedadouche, Marc Thomas, Antoine Tahan, Raynald Guilbault

“…The results demonstrate that ApEn, SampEn, and LZC provide alternative features for signal processing. A new methodology is presented combining both Kurtosis and LZC for early detection of faults. …”
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Fusion of Vibration and Current Signatures for the Fault Diagnosis of Induction Machines by Meng-Kun Liu, Minh-Quang Tran, Peng-Yi Weng

“…Among these techniques, motor current signature analysis (MCSA) and vibration analysis are two of the most common signal-based condition monitoring methods. …”
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Nonreference Medical Image Edge Map Measure by Karen Panetta, Chen Gao, Sos Agaian, Shahan Nercessian

“…Edge detection is a key step in medical image processing. …”
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Automated screening for retinopathy by A. S. Rodin, V. S. Akopyan, N. S. Semenova, A. S. Krylov

“…It was tested on dataset of 70 images with various types of pathological features (age related macular degeneration, chorioretinitis, central serous chorioretinopathy and diabetic retinopathy).Results: It was shown that the system can achieve a sensitivity of 73 % and specificity of 72 %.Conclusion: Automated detection of macular lesions using proposed software can significantly reduce manual grading workflow. …”
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MuPETFlow: multiple ploidy estimation tool from flow cytometry data by C. Gómez-Muñoz, G. Fischer

“…These features significantly accelerate the analysis, making it especially valuable for projects involving large datasets.…”
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Explainable AI for Bipolar Disorder Diagnosis Using Hjorth Parameters by Mehrnaz Saghab Torbati, Ahmad Zandbagleh, Mohammad Reza Daliri, Amirmasoud Ahmadi, Reza Rostami, Reza Kazemi

“…XAI analysis revealed that anterior brain regions in these higher frequency bands contributed most significantly to BD detection, providing new insights into the neurophysiological markers of BD. …”
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Automatic cattle identification system based on color point cloud using hybrid PointNet++ Siamese network by Pyae Phyo Kyaw, Pyke Tin, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin

“…The proposed approach employs a hybrid detection method that first applies a 2D depth image detection model before converting the detected region into a color point cloud, allowing for robust feature extraction. …”
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Building Diagnostics Options for Existing Buildings – Innovative Methods by Zsolt Szurös, Rita Rebeka Ordog, Kitti Ajtayné Károlyfi, Dóra Szalai, Ádám Bukovics

“…The evaluation of the three damage detection methodologies (Geometrical features, Color and intensity information, Combined Method) highlights their complexity, technological requirements, cost, practical applicability, and accuracy. …”
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Whole slide image based prognosis prediction in rectal cancer using unsupervised artificial intelligence by Xuezhi Zhou, Jing Dai, Yizhan Lu, Qingqing Zhao, Yong Liu, Chang Wang, Zongya Zhao, Chong Wang, Zhixian Gao, Yi Yu, Yandong Zhao, Wuteng Cao

“…Methods A total of 238 patients with rectal cancer from two datasets were collected for the development and validation of the prognostic signature. A tumor detection model was built by transfer learning. Then, on the basis of the tumor patches recognized by the tumor detection model, a convolutional autoencoder model was built for decoding the tumor patches into deep latent features. …”
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Prospects for the discovery of rich uranium ores in the Kryvorizko-Kremenchutska mineragenic zone of the Ukrainian Shield by G. A. Kalashnyk

“…The analysis of the results of hydrolithochemical investigations within the Hannivska area in the northern part of the East-Hannivska strip of the Kryvorizkiy iron ore belt is presented. …”
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Towards a phonetic history of the voices of Spanish poets by Valentina Colonna, Antonio Pamies Bertrán, Stefano Damato

“…These include variation as a consistent element among authors and within a single author, enabling the detection of main features and sub-groups; common features marking a global grouping; and the possible variety and criticism of clusters, revealing the complexity of this speech and the effectiveness of our model to describe it. …”
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Fractal Dimension Based on Morphological Covering for Ground Target Classification by Kai Du, Xiang Fang, Wei-ping Zhang, Kai Ding

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An accurate approach to discriminate android colluded malware from single app malware using permissions intelligence by Roger Yiran Mawoh, Joan Beri Ali Wacka, Franklin Tchakounte, Claude Fachkha, Kolyang

“…The experimental findings highlight the following key insights: (i) Identification of the five most significant permission features for detecting colluding applications; (ii) Positive impact of smali file size and permission rates on classification performance; (iii) Superior performance of Random Forest with a ROC_AUC of 99.48% and LightGBM with 96.91% accuracy, 96.96% precision, 96.90% recall and 96.90% F1-score compared to other classifiers; (iv) Comparative analysis with previous research demonstrates that SigColDroid, despite utilizing fewer features, outperforms state-of-the-art approaches. …”
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Prediction of heart failure risk factors from retinal optical imaging via explainable machine learning by Sona M. Al Younis, Samit Kumar Ghosh, Hina Raja, Feryal A. Alskafi, Siamak Yousefi, Siamak Yousefi, Ahsan H. Khandoker

“…Logistic regression, CatBoost, and XGBoost models demonstrated robust performance, with notable accuracy and area under the curve (AUC) scores, especially in classifying CHF and UHF. Feature importance analysis highlighted key retinal parameters, such as inner segment-outer segment to retinal pigment epithelium (ISOS-RPE) and inner nuclear layer to the external limiting membrane (INL-ELM) thickness, as crucial indicators for heart failure detection. …”
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