Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

“…Out of a total of 5,644 people tested during the COVID-19 pandemic, 5,086 people tested negative and 558 people tested positive. At the same time, support for machine vectors showed the best results in detecting coronavirus with a recall of 75 % and an F1 score of 60 % compared to models: Random drill, KNN, LR, AB, and DT.Discussion and Conclusions. …”
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Analysis of Grassland Vegetation Coverage Changes and Driving Factors in China–Mongolia–Russia Economic Corridor from 2000 to 2023 Based on RF and BFAST Algorithm by Chi Qiu, Chao Zhang, Jiani Ma, Cuicui Yang, Jiayue Wang, Urtnasan Mandakh, Danzanchadav Ganbat, Nyamkhuu Myanganbuu

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MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d’Ivoire by Fateneba Kone, Lucie Conrad, Jean T. Coulibaly, Kigbafori D. Silué, Sören L. Becker, Brama Kone, Issa Sy

“…Machine learning (ML) algorithms were employed for distinguishing P. falciparum-positive from P. falciparum-negative samples. …”
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Characterization and Selection of WiFi Channel State Information Features for Human Activity Detection in a Smart Public Transportation System by Roya Alizadeh, Yvon Savaria, Chahe Nerguizian

“…Robust methods are needed to detect how people are moving in smart public transportation systems. …”
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A Deep Learning-Driven CAD for Breast Cancer Detection via Thermograms: A Compact Multi-Architecture Feature Strategy by Omneya Attallah

“…Features from all layers of the three CNNs are subsequently incorporated, and the Minimum Redundancy Maximum Relevance (MRMR) algorithm is utilized to determine the most prominent features. …”
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Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records by Shumit Saha, Heather Ross, Pedro Elkind Velmovitsky, Chloe X. Wang, Julie K. K. Vishram-Nielsen, Cedric Manlhiot, Bo Wang, Joseph A. Cafazzo

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Unveiling Public Sentiment on Quarter Life Crisis: A Comparative Performance Evaluation of Support Vector Machine and Naïve Bayes Algorithms on Social Media X Data by Talitha Dwi Septyorini, Khothibul Umam, Maya Rini Handayani

“…This research contributes by providing empirical evidence regarding algorithm performance for sentiment analysis in mental health topics, offering recommendations for effective early detection strategies utilizing social media data.…”
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The Impact of a Line Probe Assay Based Diagnostic Algorithm on Time to Treatment Initiation and Treatment Outcomes for Multidrug Resistant TB Patients in Arkhangelsk Region, Russia... by Platon Eliseev, Grigory Balantcev, Elena Nikishova, Anastasia Gaida, Elena Bogdanova, Donald Enarson, Tara Ornstein, Anne Detjen, Russell Dacombe, Elena Gospodarevskaya, Patrick P J Phillips, Gillian Mann, Stephen Bertel Squire, Andrei Mariandyshev

“…In smear negative patients, the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 78 days when compared to the culture-based algorithm (LJ, p<0.001). …”
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Sensitivity Study of Feature Vectors Formed on the Basis of Multiple Scale Transformations of Processed Images by D. V. Vasilieva

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Development and feasibility testing of an AI-powered chatbot for early detection of caregiver burden: protocol for a mixed methods feasibility study by Ravi Shankar, Anjali Bundele, Amanda Yap, Amartya Mukhopadhyay

“…Primary outcomes include concordance between caregiver burden levels detected by the NLP algorithm and validated assessment scores at both timepoints. …”
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SCH-Hunter: A Taint-Based Hybrid Fuzzing Framework for Smart Contract Honeypots by Haoyu Zhang, Baotong Wang, Wenhao Fu, Leyi Shi

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Comparison of the STANDARD M10 C. difficile, Xpert C. difficile, and BD MAX Cdiff assays as confirmatory tests in a two-step algorithm for diagnosing Clostridioides difficile infec... by Hyunseul Choi, Minhee Kang, Sun Ae Yun, Hui-Jin Yu, Eunsang Suh, Tae Yeul Kim, Hee Jae Huh, Nam Yong Lee

“…This algorithm starts with enzyme immunoassay (EIA) for detecting glutamate dehydrogenase (GDH) and toxins A/B, followed by nucleic acid amplification test (NAAT) for GDH-positive but toxin-negative cases. …”
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Guided wave signal‐based sensing and classification for small geological structure by Hongyu Sun, Jiao Song, Shanshan Zhou, Qiang Liu, Xiang Lu, Mingming Qi

“…Abstract Sensing, Computing and Communication Integration (SC2) is widely believed as a new enabling technology. A non‐negative tensor sparse factorisation (NTSF) algorithm based on tensor analysis is proposed for sensing and classification of Small Geological Structure in coal mines. …”
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Identification of Mattic Epipedon Degradation on the Northeastern Qinghai–Tibetan Plateau Using Hyperspectral Data by Junjun Zhi, Hong Zhu, Jingwen Yang, Qiuchen Yan, Dandan Zhi, Zhongbao Sun, Liangwei Ge, Chengwen Lv

“…The characteristic bands were concentrated in the visible light range (446–450 nm) and short-wave infrared range (2134 nm, 2267–2269 nm), which are closely related to the spectral responses of organic carbon and mineral components. (2) Spectral reflectance was significantly negatively correlated with moisture content, and model accuracy decreased as moisture content increased. (3) After correction using the EPO algorithm, the model accuracy for the high-moisture group improved by 13.2–16.7%, whereas that for the low-moisture group (<15%) decreased by 7.5%, verifying 15% moisture content as the critical threshold for water interference. …”
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Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG by Thais de Andrade Silva, Gabriel Fernandes Souza dos Santos, Adilson Ribeiro Prado, Daniel Cruz Cavalieri, Arnaldo Gomes Leal Junior, Flávio Garcia Pereira, Camilo A. R. Díaz, Marco Cesar Cunegundes Guimarães, Servio Túlio Alves Cassini, Jairo Pinto de Oliveira

“…This work reports an efficient method to detect SARS-CoV-2 antibodies in blood samples based on SERS combined with a machine learning tool. …”
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Performance of the Oncuria-Detect bladder cancer test for evaluating patients presenting with haematuria: results from a real-world clinical setting by Ian Pagano, Zhen Zhang, Michael Luu, Sergei Tikhonenkov, Florence Le Calvez-Kelm, Steve Goodison, Toru Sakatani, Kaoru Murakami, Takashi Kobayashi, Patrice Avogbe, Howard Kim, Riko Lee, Arnaud Manel, Emmanuel Vian, Charles J. Rosser, Hideki Furuya

“…In the test set, the Oncuria-Detect assay correctly identified bladder cancer in 62 of 73 cases resulting in a sensitivity of 85%, a specificity of 72%, and a negative predictive value (NPV) of 95%. …”
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Early Perspectives on the Planned Brazilian Program to Address Ship-Sourced Pollution by Daniel Constantino Zacharias, Angelo Teixeira Lemos

“…The system incorporates a range of technologies, such as satellite data, AI algorithms, autonomous sensors, and high-resolution modeling, to detect and respond to oil spills and maritime threats. …”
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Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain by Fàtima Della Bellver, Belen Franch Gras, Italo Moletto-Lobos, César José Guerrero Benavent, Alberto San Bautista Primo, Constanza Rubio, Eric Vermote, Sebastien Saunier

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A reliable score-based routing protocol using a fog-assisted intrusion detection system in vehicular ad-hoc networks by Samira Tahajomi Banafshehvaragh, Mani Zarei, Amir Masoud Rahmani

“…The IDS is trained using three machine learning-based algorithms and a voting technique to reduce false detection. …”
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Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning by Faisal Bin Al Abid, Aryati Binti Bakri, Md. Golam Rabiul Alam, Jia Uddin, Shefayatuj Johara Chowdhury

“…Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. …”
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