Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…Robust detection of prostatic cancer is a challenge due to the multitude of variants and their representation in MR images. …”
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Light scattering-based screening method for rapid evaluating antibiotic effects on bacteria using laser speckle imaging by Donghyeok Kim, Seongjoon Moon, Jongseo Lee, Kyoungman Cho, Changhan Lee, Jonghee Yoon

“…The image processing algorithm analyzes correlation contrast in time-series laser speckle images, enabling more precise bacterial activity detection compared to conventional LSI techniques. …”
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CENPF as a Potential Biomarker Associated with the Immune Microenvironment of Renal Cancer by Meilin Chen MS, Xiuxin Tang MS, YanPing Liang MD, Tangdang Ding MS, Meifang He PhD, Dong Wang PhD, Ruizhi Wang PhD

“…Single-cell sequencing data from the GSE159115 dataset were analyzed, and the CIBERSORT algorithm was applied to evaluate the composition of tumor immune infiltrating cells (TIICs). …”
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Sentiment Analysis on Tabungan Perumahan Rakyat (TAPERA) Program by using Support Vector Machine (SVM) by Rizki Agam Syahputra, Riski Arifin, Suryadi ., Muhammad Iqbal

“…This indicates that the model is highly effective in classifying sentiments, particularly in identifying negative sentiments. The resulting confusion matrix shows the model's excellent performance in detecting negative sentiments, with no False Positives (FP) and a very high number of True Negatives (TN). …”
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Klasifikasi Tingkat Stress dari Data Berbentuk Teks dengan Menggunakan Algoritma Support Vector Machine (SVM) dan Random Forest by Naufal Fathirachman Mahing, Alifi Lazuardi Gunawan, Ahmad Foresta Azhar Zen, Fitra Abdurrachman Bachtiar, Satrio Agung Wicaksono

“…High levels of stress can have a negative impact on human health. Early detection of stress is something that is very important to do. …”
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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…In this contribution, we propose a novel parallel patch-wise sparse residual learning (P²SR) algorithm for resolution enhancement based on fusion of HSI and MSI. …”
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Comparison of Manhattan and Chebyshev Distance Metrics in Quantum-Based K-Medoids Clustering by Solikhun Solikhun, Muhammad Rahmansyah Siregar, Lise Pujiastuti, Mochamad Wahyudi, Deny Kurniawan

“…This makes it more suitable for medical applications where false negatives carry high risks, such as disease detection, despite its higher cost and mean squared error (MSE). …”
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Comparative Analysis of Single‐ and Dual‐Marker Strategies for Rapid Non–ST‐Segment–Elevation Myocardial Infarction Rule‐Out Using Cardiac Myosin‐Binding Protein C, Copeptin, and H... by Mustafa Yildirim, Christian Salbach, Matthias Mueller‐Hennessen, Norbert Frey, Evangelos Giannitsis

“…DMS protocols showed negative predictive values of 99.1% to 100%, comparable with the European Society of Cardiology algorithms (99.3%–100%). …”
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Lithium Battery Thermal Runaway Warning Method Based on Multi-Feature Fusion by Mingwei DAI, Chunfu ZHANG, Jiawu YANG

“…[Conclusion] The early warning algorithm is able to accurately identify lithium batteries with abnormal temperature rise rates, and can promptly and precisely detect the timing and location of the opening of the safety valve in the lithium battery. …”
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”My AI is Lying to Me”: User-reported LLM hallucinations in AI mobile apps reviews by Rhodes Massenon, Ishaya Gambo, Javed Ali Khan, Christopher Agbonkhese, Ayed Alwadain

“…Using a mixed-methods approach, a heuristic-based User-Reported LLM Hallucination Detection algorithm were applied to identify  20,000 candidate reviews, from which 1,000 are manually annotated. …”
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Limbal stem cell deficiency diagnostics by B.E. Malyugin, S.A. Borzenok, S.Yu. Kalinnikova, M.Yu. Gerasimov

“…One of the important problems is the lack of a clear diagnostic algorithm and a standardized set of diagnostic techniques for this condition. …”
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Distinguishing glioblastoma from brain metastasis; a systematic review and meta-analysis on the performance of machine learning by Mohammad Amin Habibi, Reza Omid, Shafaq Asgarzade, Sadaf Derakhshandeh, Ali Soltani Farsani, Zohreh Tajabadi

“…We systematically reviewed the studies reported the performance of machine learning (ML) algorithms for accurately discrimination of these two entities. …”
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Surface ozone trend variability across the United States and the impact of heat waves (1990–2023) by K.-L. Chang, K.-L. Chang, B. C. McDonald, C. Harkins, C. Harkins, O. R. Cooper

“…<p>This paper outlines a comprehensive trend assessment of surface ozone observations across the conterminous USA over 1990–2023. A change point detection algorithm is applied to evaluate seasonal trends at various percentiles. …”
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Comparative estimation of the effectiveness of the Khorana, Vienna CATS, and TiC-Onco scores and the vWF/ADAMTS13 ratio in identifying a high risk of thrombotic complications in pa... by A. V. Vorobеv, A. G. Solopova, V. O. Bitsadze, M. M. Baeva, M. E. Sosnyagova, V. N. Galkin, D. O. Utkin, A. D. Makatsariya

“…The Vienna CATS score, due to the inclusion of the D-dimer level, demonstrated a slightly higher detection rate of true thrombogenic cases (54.2% instead of 50%); however, the performance of this score in differentiation between false positive and false negative cases was not always high. …”
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Robust Predictive Maintenance for Robotics via Unsupervised Transfer Learning by Arash Golibagh Mahyari, Thomas locher

“…The deployment of the proposed algorithm on real-world datasets demonstrates that the algorithm can not only distinguish between tasks and mechanical condition change, it further yields a sharper deviation from the trained model in case of a mechanical condition change and thus detects mechanical issues with higher confidence.…”
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Multiclass Supervised Learning Approach for SAR-COV2 Severity and Scope Prediction: SC2SSP Framework by Shaik Khasim Saheb, B. Narayanan, T.V. Narayana Rao

“…Results: The model utilizes the Exact Greedy Algorithm to classify the spread and impact of the virus in different regions. …”
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Bilateral Condylar Hyperplasia: Importance of Its Diagnosis in the Treatment and Long-Term Stability of Skeletal Class III Correction by Diego Fernando López, Martín Fernando Orozco, Sofia Ochoa Gómez, Santiago Herrera Guardiola, Luis Eduardo Almeida

“…This study aims to propose a therapeutic algorithm for diagnosing and treating bilateral condylar hyperplasia (BCH) based on demographic, clinical, craniofacial growth, and clivus ratio uptake conditions. …”
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Integrated rapid risk assessment for dengue fever in settings with limited diagnostic capacity and uncertain exposure: Development of a methodological framework for Tanzania. by Matthias Hans Belau, Juliane Boenecke, Jonathan Ströbele, Mirko Himmel, Daria Dretvić, Ummul-Khair Mustafa, Katharina Sophia Kreppel, Elingarami Sauli, Johanna Brinkel, Ulfia Annette Clemen, Thomas Clemen, Wolfgang Streit, Jürgen May, Amena Almes Ahmad, Ralf Reintjes, Heiko Becher

“…<h4>Results</h4>The result of the suspected case refinement algorithm for clinically defined syndromic cases was consistent with the laboratory-confirmed diagnosis (dengue yes or no). …”
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Transabdominal ultrasound for the characterization and follow-up of cystic pancreatic lesions by Julian Seelig, Maria Heni, Max Seitzinger, Kien Vu Trung, Jürgen Feisthammel, Marcus Hollenbach, Robert Henker, Albrecht Hoffmeister, Jonas Rosendahl, Valentin Blank, Thomas Karlas

“…Univariate and multiple logistic regression analyses were used to identify determinants for the detection of CPL via TAUS. Cross-method morphological assessments were analysed, and a patient-specific algorithm for selecting the appropriate monitoring method was developed. …”
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A Clinical Validation of a Diagnostic Test for Esophageal Adenocarcinoma Based on a Novel Serum Glycoprotein Biomarker Panel: PromarkerEso by Jordana Sheahan, Iris Wang, Peter Galettis, David I. Watson, Virendra Joshi, Michelle M. Hill, Richard Lipscombe, Kirsten Peters, Scott Bringans

“…PromarkerEso identified individuals with and without EAC (96% and 95% positive and negative predictive values). Conclusions: This less invasive approach for EAC detection with the novel combination of these glycoprotein biomarkers and clinical factors coalesces in a potential step toward improved diagnosis.…”
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