Modality-based Modeling with Data Balancing and Dimensionality Reduction for Early Stunting Detection by Yohanes Setiawan, Mohammad Hamim Zajuli Al Faroby, Mochamad Nizar Palefi Ma’ady, I Made Wisnu Adi Sanjaya, Cisa Valentino Cahya Ramadhani

“…The main contributions of this research are the development of a comprehensive framework for modality-based analysis, the application of advanced data preprocessing techniques, and the comparison of various machine learning algorithms to identify the best model for stunting detection. …”
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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. …”
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Patterns of care for people presenting to Australian general practice with musculoskeletal complaints based on routinely collected data: protocol for an observational cohort study... by Alexandra Gorelik, Romi Haas, Ljoudmila Busija

“…Previous studies using routinely collected health data for research have not consistently reported the codes and algorithms used to describe the population, exposures, interventions and outcomes in sufficient detail to allow replication. …”
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Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…However, until now, no work has systematically evaluated the performance of various categories of gait features for alcohol intoxication detection task using traditional machine learning algorithms. This study evaluates 27 signal processing features handcrafted from accelerometer gait data across five domains: time, frequency, wavelet, statistical, and information-theoretic. …”
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Design, assembly, alignment and application of a versatile, open-source, single-pixel microscope by Samuel I. Zapata-Valencia, Heberley Tobón-Maya, Luis Ordoñez, Andrea Farina, Jesús Lancis, Enrique Tajahuerce

“…After interaction with the sample, light is collected by a bucket detector, and the image is reconstructed through computational algorithms, such as basis transformations or compressive sensing. …”
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A novel Hadamard matrix based hybrid compressive sensing technique for enhancing energy efficiency and network longevity by Balamurali S, Kathirvelu M, SatheeshKumar Palanisamy, Tagrid Abdullah N. Alshalali

“…To address these challenges, integrating excellent data compression and reconstruction methods with high-quality clustering algorithms can be the ideal solution. The proposed approach, NHM-HCS (Novel Hadamard Matrix-based Hybrid Compressive Sensing) introduces a collaborative method incorporating data compression, efficient cluster head selection, and optimal routing. …”
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Screening and validation of diagnostic markers for keloids via bioinformatics analysis by Ze Wang, Bo Hu, Wenfei Li, Tengxiao Ma, Lei Li

“…Methods: The GSE44270, GSE145725, GSE7890 and GSE83286 datasets were analyzed in combination with difference analysis and weighted gene coexpression network analysis (WGCNA) and machine learning algorithms, candidate genes related to KD were screened and verified via receiver operating characteristic (ROC) curves and external datasets. …”
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Verification of the method for classifying the technical state of a turboshaft engine fuel regulator in the space of operational process parameters under factory test conditions by Ihor Ohanian, Sergiy Yepifanov

“…Recommendations for further improvement of the method include using expert systems and developing effective model identification algorithms. The method can be recommended for integration into production technologies for condition-based maintenance to improve diagnostic accuracy and optimize repair activities.…”
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Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). …”
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Evaluating the Signal Contribution of the DTU21MSS on Coastal Mean Dynamic Topography and Geostrophic Current Modeling: A Case Study in the African–European Region by Hongkai Shi, Xiufeng He, Ole Baltazar Andersen

“…With the accumulation of synthetic aperture radar (SAR) altimetry data and advancements in retracking algorithms, the improved along-track spatial resolution and signal-to-noise ratio have significantly enhanced the availability and precision of sea surface height (SSH) measurements, particularly in challenging environments such as coastal areas, ocean currents, and polar regions. …”
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Sulfur fumigation of botanical drugs: impact on chemical composition and pharmacological properties, and advances in detection technologies by Weiyi Xu, Hongyu Jin, Ying Wang, Feng Wei, Jing Liu

“…In recent years, researchers have created various innovative detection technologies, including fluorescent probe rapid detection methods and machine learning algorithms, to improve the precision of identifying and quantifying chemical changes in sulfur-fumigated samples. …”
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Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response by Mohsen Moosavi, Javad Olamaei, Hossein Mohmmadnezhad Shourkaei

“…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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Progress on the world’s primate hotspots and coldspots: modeling ensemble super SDMs in cloud-computers based on digital citizen-science big data and 200+ predictors for more susta... by Moriz Steiner, Falk Huettmann

“…These Super SDMs are conducted using an ensemble of modern Machine Learning algorithms, including Maxent, TreeNet, RandomForest, CART, CART Boosting and Bagging, and MARS with the utilization of cloud supercomputers (as an add-on option for more powerful models). …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…The plugin’s modular design enables seamless integration without requiring modifications to existing OCR algorithms, while its feedback mechanism adapts to domain-specific terminology and user preferences. …”
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Comparison of ileus risk in selected second-generation antipsychotics based on FAERS database by Yaqian Tan, Hui Xia, Qi Song

“…In disproportionality analysis, the algorithms of reporting odds ratio (ROR) and information component (IC) were applied for ileus risk signal detection. …”
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Movement Disorders and Smart Wrist Devices: A Comprehensive Study by Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

“…Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. …”
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Machine learning approaches for identifying and predicting voltage conditions in power system networks using network topology behavior input formulation by Tolulope David Makanju, Oluwole John Famoriji, Ali N. Hasan, Thokozani Shongwe

“…Different machine learning algorithms random forest, support vector machine and gradient boosting were used to evaluate the input formulation approach for voltage condition prediction in power system networks. …”
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Molecular survey of cattle ticks in Burundi: First report on the presence of the invasive Rhipicephalus microplus tick. by Lionel Nyabongo, David O Odongo, Gad Milton, Eunice Machuka, Patrick Vudriko, Roger Pelle, Esther G Kanduma

“…Phylogenetic relationships were inferred using bayesian and maximum likelihood algorithms. A total of 483 ticks were collected from the five AEZs sampled. …”
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Analysis of student’s final qualification theses using text loans detection systems by D. A. Petrusevich, K. D. Shakhardin

“…It seems that these differences can be explained with different text search and analyze algorithms. The dependencies between the Rucontext percentage and the Antiplagiat text loan percentage is presented.…”
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Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan. by Ana Torres, Brima Musa Younis, Samuel Tesema, Jose Carlos Solana, Javier Moreno, Antonio J Martín-Galiano, Ahmed Mudawi Musa, Fabiana Alves, Eugenia Carrillo

“…This approach could prove instrumental to train future supervised algorithms based on larger patient cohorts both for a more precise diagnosis and to gain insight into fundamental aspects of this complication of visceral leishmaniasis.…”
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