Measuring countries relative efficiencies in using development assistance: a data envelopment analysis approach by Mohamed F. Sakr, Kamal Samy Selim, Sherin Gamaleldin Taha

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Machine learning in biomedical and health big data: a comprehensive survey with empirical and experimental insights by Kamal Taha

“…Abstract This article delves into the application of machine learning within the realm of biomedical and health big data. We present both empirical and experimental assessments of diverse machine learning methodologies, providing a comprehensive examination of current techniques in big data analytics. …”
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Weightage Identified Network of Keywords Technique: A Structured Approach in Identifying Keywords for Systematic Reviews by Sasidharan Sivakumar, Gowardhan Sivakumar

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Forecasting Cancer Incidence in Canada by Age, Sex, and Region Until 2026 Using Machine Learning Techniques by Ehsan Kaviani, Kalpdrum Passi

“…This study analyzes cancer trends in Canada using machine learning techniques to extract insights from extensive cancer data sourced from the Canadian Cancer Society and Statistics Canada. …”
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Inland wetlands mapping and vulnerability assessment using an integrated geographic information system and remote sensing techniques by C.E. Akumu, J. Henry, T. Gala, S. Dennis, C. Reddy, F. Tegegne, S. Haile, R.S. Archer

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Decision model for determining the ownership structure of chemical park units, Integration of decision-making techniques and data envelopment analysis by Darush Mohamadi Zanjirani

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Modelling the Isotope composition of groundwater using hydrochemical properties in eastern Saudi Arabia: Implementation of innovative data intelligence techniques by Mohammed Benaafi, Waleed M. Hamanah, Ebrahim Al-Wajih

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Filling-well: An effective technique to handle incomplete well-log data for lithology classification using machine learning algorithms by Sherly Ardhya Garini, Ary Mazharuddin Shiddiqi, Widya Utama, Alif Nurdien Fitrah Insani

“…In contrast, KNN struggled with missing-not-at-random (MNAR) data due to its reliance on the k parameter and distance metric, making it less effective in mapping missing data relationships. • Missing values in well-log data can hinder lithology classification accuracy for efficient resource exploration in the oil and gas industry. • This research aims to address the problem of missing values in well-log datasets by applying machine learning algorithms such as XGBoost, ANN, and KNN to enhance classification performance. • XGBoost demonstrated superior performance in handling extreme missing data (30 %) in well-log datasets. …”
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Big Data and Security: A Review of Social Media Risks and Insights for Indonesia by Ahmad Harakan, Abdillah Abdillah, Try Gustaf Said, Mujizatullah Mujizatullah, Simon Gray

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Evaluating techniques from low-shot learning on traditional imbalanced classification tasks by Preston Billion-Polak, Taghi M. Khoshgoftaar

“…Abstract Recent advances in machine learning have resulted in techniques that are effective in complex scenarios, such as those with many rare classes or with multimodal data; in particular, low-shot learning (LSL) is a challenging task for which multiple strong approaches have been developed. …”
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An Assessment of Land Use Land Cover Using Machine Learning Technique by V. Pushpalatha, H. N. Mahendra, A. M. Prasad, N. Sharmila, D. Mahesh Kumar, N. M. Basavaraju, G. S. Pavithra and S. Mallikarjunaswamy

“…This research paper presents a comprehensive assessment of the built-up area in Mysuru City over the decade spanning from 2010 to 2020, employing advanced geospatial techniques. The study aims to analyze the spatiotemporal patterns of urban expansion, land-use dynamics, and associated factors influencing the city’s built environment. …”
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Exploring machine learning for fake news detection: techniques, tools, challenges, and future research directions by Sapana Yakkundi, Rudragoud Patil, Sangeeta Sangani, R. H. Goudar, Swetha Indudhar Goudar, Aijazahamed Qazi

“…Abstract Social media usage has reached its peak across all age groups, resulting in vast quantities of data being generated daily, some internet users disseminate fake information for their own benefit. …”
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Assessing Survey Data to Study Traffic Flow Characteristics: An in-depth analysis of King Fahad Road, Al-Ahsa, Saudi Arabia by Md Kamrul Islam, Abdulaziz Ibrahim Mohammed Al-Muaybid, Muath Fahad Abdullah Al-Saqer, Mohammed Saleh Rashid Al-Nagada, Khaled Saleh Abdulaziz Al-Newaihel, Rocksana Akter, Muhammad Aniq Gul, Muhammad Muhitur Rhaman, Ziad Shatnawi

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Predicting CO2 adsorption in KOH-activated biochar using advanced machine learning techniques by Raouf Hassan, Alireza Baghban

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Improving Multi-label Classification Performance on Imbalanced Datasets Through SMOTE Technique and Data Augmentation Using IndoBERT Model by Leno Dwi Cahya, Ardytha Luthfiarta, Julius Immanuel Theo Krisna, Sri Winarno, Adhitya Nugraha

“…The classification model employed is the IndoBERT model. Both oversampling techniques can address data imbalance by generating synthetic and new data. …”
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Exploring RNA-Seq Data Analysis Through Visualization Techniques and Tools: A Systematic Review of Opportunities and Limitations for Clinical Applications by Farhana Manzoor, Cyruss A. Tsurgeon, Vibhuti Gupta

“…This review aims to outline the current state-of-the-art data visualization techniques and tools commonly used to frame clinical inferences from RNA-seq data and point out their benefits, applications, and limitations. …”
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Assessing particulate matter (PM2.5) concentrations and variability across Maharashtra using satellite data and machine learning techniques by Ganesh Machhindra Kunjir, Suvarna Tikle, Sandipan Das, Masud Karim, Sujit Kumar Roy, Uday Chatterjee

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A systematic review of studies that aim to determine which outcomes to measure in clinical trials in children. by Ian Sinha, Leanne Jones, Rosalind L Smyth, Paula R Williamson

“…Two groups utilised the Delphi technique, one used the nominal group technique, and one used both methods to reach a consensus about which outcomes should be measured in clinical trials. …”
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Cluster Optimization for Exponential, Right-Triangular, and Uniformly Distributed Data by Gabiriele Bulivou, Karuna G. Reddy, M. G. M. Khan

“…Cluster analysis aims to categorize data objects into cohesive groups based on their intrinsic characteristics, often modeled by probability distributions. …”
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A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data by Jumana Hasina, Aman Mwafy

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