Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…This review provides a comprehensive overview of cloud detection algorithms based on deep learning from the perspective of semantic segmentation, and elaborates on the research progress, advantages, and limitations of different categories in this field. …”
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A new iterative multi-step method for solving nonlinear equation by Muhammad Usman, Javed Iqbal, Alamgir Khan, Ikram Ullah, Hasib Khan, Jehad Alzabut, Hisham Mohammad Alkhawar

“…The findings reveal that the proposed technique surpasses several renowned iterative methods in both accuracy and computational efficiency. • High-order convergence: The method demonstrates a sixteenth-order convergence rate, requiring just five function evaluations per iteration, which enhances computational efficiency. • Derivative-free approach: The algorithm employs finite difference approximations, eliminating the need for second derivative calculations and increasing its applicability to complex problems. • Numerical validation: Comprehensive numerical tests and comparative studies validate the exceptional accuracy and efficiency of the proposed iterative approach.…”
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Advanced quantification pipeline reveals new spatial and temporal tumor characteristics in preclinical multiple myeloma by Zhixin Sun, Jacqueline M. Godbe, Alexander Zheleznyak, Brad Manion, Junhao Hu, Julie L. Prior, Kathleen Duncan, Ulugbek S. Kamilov, Monica Shokeen

“…Conclusions This pipeline enables reproducible, anatomically precise quantification of region-specific trends in MM progression, including joint-specific lesion tropism and sex-based differences, from longitudinal PET/CT scans. By mitigating common challenges such as excretion artifacts and inconsistent mouse positioning, our approach overcomes limitations of manual analysis and enhances evaluation of tumor biology and treatment response in preclinical models of bone-involved cancers. …”
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A Cone-Beam Computed Tomography-Based Assessment of Safe Zones for Orthodontic Mini-Implant Placement in the Lateral Maxilla: A Retrospective Morphometric Study by Iva Jakovljevic, Pavle Milanovic, Milica Vasiljevic, Jovana Milanovic, Momir Z. Stevanovic, Nemanja Jovicic, Milos Stepovic, Vladimir Ristic, Dragica Selakovic, Gvozden Rosic, Aleksandra Arnaut

“…CBCT scans (sagittal and axial cross-sections) were used to evaluate interdental bone characteristics in different regions. …”
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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…A leave-one-out cross-validation strategy was used for model training and evaluation. We tested seven different algorithms: K-Nearest Neighbors, Decision Tree, Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Logistic Regression. …”
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Identification of a PANoptosis-related long noncoding rna risk signature for prognosis and immunology in colon adenocarcinoma by Yuekai Cui, Jie Mei, Shengsheng Zhao, Bingzi Zhu, Jianhua Lu, Hongzheng Li, Binglong Bai, Weijian Sun, Wenyu Jin, Xueqiong Zhu, Shangrui Rao, Yongdong Yi

“…Using the CIBERSORT algorithm and gene set enrichment analysis, variations in infiltrating immune cells and immune processes were observed between the two risk groups. …”
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Coverage intensity of optimal sensors for common, isolated, and integrated steel structures using novel approach of FEM-MAC-TTFD by Mehdi Firoozbakht, Hamidreza Vosoughifar, Alireza Ghari Ghoran

“…In this article, a novel algorithm for optimal sensor placement in various steel frames was evaluated. …”
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Correction of TRMM 3B43 Monthly Precipitation Data Using Quantile Regression Model in the Urmia Lake Basin by Sima Kazempour Choursi, Mahdi Erfanian, Hirad Abghari, Mirhassan Miryaghoobzadeh, khadijeh Javan

“…Remote sensing, such as the TRMM 3B43, can provide a more accurate spatial distribution of rainfall, particularly in regions that lack rain gauge stations. The TRMM 3B43 algorithm is aimed at providing the most precise rainfall estimates by utilizing a combination of multi-sensor measurements gathered from different satellites. …”
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Optimal design of agro-residue filled poly(lactic acid) biocomposites using an integrated CRITIC-CoCoSo multi-criteria decision-making approach by László Lendvai, Sándor Kálmán Jakab, Tej Singh

“…The algorithm considered several attributes, including mechanical traits evaluated via tensile, flexural, and impact tests, hardness, water absorption, biodegradation, and production cost. …”
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Radionuclide Diagnosis of Esophageal Dysmotility and Gastroesophageal Reflux in Patients with Systemic Sclerosis by R. A. Bashirov, L. E. Samoilenko, S. A. Ryzhkin, K. F. Vartanyan, D. A. Gimaletdinova, A. F. Yusupova, D. I. Abdulganieva, L. F. Ziganshina, E. S. Zamanova, E. V. Puzakin, A. A. Malov, B. M. Sharafutdinov

“…Scans were analyzed using visual assessment, quantitative estimation of time/activity curves, and a proposed three-point scale for evaluating ED and GER severity. The control group consisted of 19 practically healthy individuals who underwent a routine examination to exclude digestive system and gastrointestinal tract diseases, the algorithm of which included dynamic scintigraphy.Results. …”
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Measuring Dyed Fiber Color with MSFU-K Microscope Spectrophotometer: Methodology Validation by Galina I. Bebeshko, Irina P. Lyubetskaya, Lidiya P. Brunova, Marina A. Khanukaeva, Georgii G. Omel'yanyuk

“…The expert determines whether the textile fibers submitted for analysis match in color or not, depending on the results of spectral comparison.The proposed validation experiment algorithm is designed for evaluating uncertainty in optical density measurements and the level of expert competence.In this case uncertainty corresponds to reproducibility standard deviation. …”
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A data management system for precision medicine. by John J L Jacobs, Inés Beekers, Inge Verkouter, Levi B Richards, Alexandra Vegelien, Lizan D Bloemsma, Vera A M C Bongaerts, Jacqueline Cloos, Frederik Erkens, Patrycja Gradowska, Simon Hort, Michael Hudecek, Manel Juan, Anke H Maitland-van der Zee, Sergio Navarro-Velázquez, Lok Lam Ngai, Qasim A Rafiq, Carmen Sanges, Jesse Tettero, Hendrikus J A van Os, Rimke C Vos, Yolanda de Wit, Steven van Dijk

“…LogiqSuite is certified and compliant with international medical data and privacy legislations. This paper evaluates a MedDMS in five types of use cases for precision medicine, ranging from data collection to algorithm development and from implementation to integration with real-world data. …”
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AI-Based Noise-Reduction Filter for Whole-Body Planar Bone Scintigraphy Reliably Improves Low-Count Images by Csaba Csikos, Sándor Barna, Ákos Kovács, Péter Czina, Ádám Budai, Melinda Szoliková, Iván Gábor Nagy, Borbála Husztik, Gábor Kiszler, Ildikó Garai

“…<b>Methods</b>: The performance of the AI bone-scan filter (BS-AI filter) in question was retrospectively evaluated on 47 different patients’ ^99mTc-MDP bone scintigraphy image pairs (anterior- and posterior-view images), which were obtained in such a manner as to represent the diverse characteristics of the general patient population. …”
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Associations of greenhouse gases, air pollutants and dynamics of scrub typhus incidence in China: a nationwide time-series study by Haoyue Cao, Jianqiang Han, Weiming Hou, Juxiang Yuan

“…Second, four statistical methods were used to assess the correlation and lag effects across different age groups and epidemic periods. Deep learning algorithms were employed to evaluate the predictive effect of environmental factors on the incidence of scrub typhus. …”
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4-D ERT monitoring of oil spill contamination dynamics and remediation planning in southern Nigeria by Stanley Uchechukwu Eze, Difference Odeyovwi Ogagarue, Juyeon Jeong, Myung Jin Nam, Omafume M. Orji, Williams N. Ofuyah

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Cardiovascular risk factors in patients with calcium pyrophosphate crystal deposition disease by M. S. Eliseev, O. V. Zhelyabina, M. N. Chikina, A. M. Novikova

“…Calcium pyrophosphate  crystal deposition disease (CPCDD) is among the most common  inflammatory rheumatic diseases; however, studies of cardiovascular risks in CPCDD have not been conducted.Objective: to stratify a cardiovascular risk in patients with CPCDD according to the systematic coronary risk evaluation (SCORE)  algorithm that allows determination of an individual 10-year risk of cardiovascular death.Subjects and methods. …”
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A systematic review of machine learning and deep learning approaches in plant species detection by Deepti Barhate, Sunil Pathak, Bhupesh Kumar Singh, Amit Jain, Ashutosh Kumar Dubey

“…Classifiers and other machine learning and deep learning algorithms that can accurately categorize and extract data can be further developed. …”
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SB‐YOLO‐V8: A Multilayered Deep Learning Approach for Real‐Time Human Detection by Prince Alvin Kwabena Ansah, Justice Kwame Appati, Ebenezer Owusu, Edward Kwadwo Boahen, Prince Boakye‐Sekyerehene, Abdullai Dwumfour

“…ABSTRACT Over the past decade, significant advancements in computer vision have been made, primarily driven by deep learning‐based algorithms for object detection. However, these models often require large amounts of labeled data, leading to performance degradation when applied to tasks with limited data sets, particularly in scenarios involving moving objects. …”
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Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques by Juswin Sajan John, Boppuru Rudra Prathap, Gyanesh Gupta, Jaivanth Melanaturu

“…Building on existing literature, discussions with psychologists and other mental health practitioners, we developed a taxonomy of 27 distinctive markers spread across 4 label categories; aiming to create a preliminary screening tool leveraging textual data.The core objective is to identify the most suitable model for this complex task, encompassing comprehensive evaluation of various machine learning and deep learning algorithms. we experimented with support vector machines (SVM), random forest (RF) and long short-term memory (LSTM) algorithms incorporating various feature combinations involving Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA). …”
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A systematic review on sleep stage classification and sleep disorder detection using artificial intelligence by Tayab Uddin Wara, Ababil Hossain Fahad, Adri Shankar Das, Md Mehedi Hasan Shawon

“…The Neural Network algorithms are the most popular, having 47 % of the total usage. …”
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