An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…This improves both the precision and efficiency of convergence while reducing the likelihood of the “two steps forward, one step back” phenomenon. This problem offers a more precise solution. …”
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Vegetable Fields Mapping in Northeast China Based on Phenological Features by Jialin Hu, Huimin Lu, Kaishan Song, Bingxue Zhu

“…Second, spectral analysis was integrated with three machine learning classifiers, which leveraged phenological and spectral features extracted from satellite images to accurately identify vegetable-growing areas. …”
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Fusion Text Representations to Enhance Contextual Meaning in Sentiment Classification by Komang Wahyu Trisna, Jinjie Huang, Hengyu Liang, Eddy Muntina Dharma

“…This step is critical as it affects the quality of the data being processed by the deep learning model. …”
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Vertically Recurrent Neural Networks for Sub‐Grid Parameterization by P. Ukkonen, M. Chantry

“…Abstract Machine learning has the potential to improve the physical realism and/or computational efficiency of parameterizations. …”
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Using recurrent neural network to estimate irreducible stochasticity in human choice behavior by Yoav Ger, Moni Shahar, Nitzan Shahar

“…First, we used computer simulation in the context of reinforcement learning to demonstrate that RNNs can be used to identify model misspecification in simulated agents with varying degrees of behavioral noise. …”
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School leader engagement in strategies to support effective implementation of an SEL program by Karen L. Thierry, Tia E. Kim, Amanda Page, Haleigh Randall

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Fetal-BET: Brain Extraction Tool for Fetal MRI by Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus, Ali Gholipour

“…Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. …”
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D2LFS2Net: Multi‐class skin lesion diagnosis using deep learning and variance‐controlled Marine Predator optimisation: An application for precision medicine by Veena Dillshad, Muhammad Attique Khan, Muhammad Nazir, Oumaima Saidani, Nazik Alturki, Seifedine Kadry

“…Instead of flipping and rotating data, the outputs from the middle phases of the hybrid enhanced technique are employed for data augmentation in the next step. Next, two pre‐trained deep learning models, MobileNetV2 and NasNet Mobile, are trained using deep transfer learning on the upgraded enriched dataset. …”
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Integrating interactive response systems and deliberate practice in a level design for games course: effects on intrinsic motivation, design anxiety, self-efficacy, and learning ac... by Kai-Ming Yang

“…This study aimed to improve student learning outcomes by integrating an interactive response system (IRS) and deliberate practice (DP) into a Level Design for Games course. …”
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Development of An Android-Based Physics E-Book with A Scientific Approach to Improve The Learning Outcomes of Class X High School Students on Impulse and Momentum Materials by Y A A Ndoa, D P Anastasia, J Jumadi

“…Results based on 4D model steps are (1) Define to produce an analysis of the needs of students during online learning, (2) Design to produce a product, namely a physics e-book, and (3) Develop to produce validation and the final product, and (4) Deploy of products is distributed in a limited way to physics teachers in Jatinom Senior High School. …”
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Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review by Md Shofiqul Islam, Fahmid Al Farid, F. M. Javed Mehedi Shamrat, Md Nahidul Islam, Mamunur Rashid, Bifta Sama Bari, Junaidi Abdullah, Muhammad Nazrul Islam, Md Akhtaruzzaman, Muhammad Nomani Kabir, Sarina Mansor, Hezerul Abdul Karim

“…This article provides a meticulous and comprehensive review of imaging-based SARS-CoV-2 diagnosis using deep learning techniques up to May 2024. This article starts with an overview of imaging-based SARS-CoV-2 diagnosis, covering the basic steps of deep learning-based SARS-CoV-2 diagnosis, SARS-CoV-2 data sources, data pre-processing methods, the taxonomy of deep learning techniques, findings, research gaps and performance evaluation. …”
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Deep learning-based identification and localization of intracranial hemorrhage in patients using a large annotated head computed tomography dataset: A retrospective multicenter stu... by Jingjing Liu, Weijie Fan, Yi Yang, Qi Peng, Bingjun Ji, Luxing He, Yang Li, Jing Yuan, Wei Li, Xianqi Wang, Yi Wu, Chen Liu, Qingfang Gong, Mi He, Yeqin Fu, Dong Zhang, Si Zhang, Yongjian Nian

“…Background: Accurately identifying and localizing the five subtypes of intracranial hemorrhage (ICH) are crucial steps for subsequent clinical treatment; however, the lack of a large computed tomography (CT) dataset with annotations of the categorization and localization of ICH considerably limits the development of deep learning-based identification and localization methods. …”
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Desarrollo de medios de aprendizaje para un gran juego de pelota basado en el aprendizaje en línea para estudiantes de secundaria vocacional de clase XI: viabilidad y eficacia (Dev... by Amran Amran, Wawan Sundawan Suherman, Ali Satia Graha, Rizqie Auliana, Ardi Riyana, Ari Tri Astuti, Desy Yunita Utami, Kukuh Wahyudin Pratama, Azhar Ramadhana Sonjaya, Asep Angga Permadi, Z. Arifin, Manil Karakauki, Syed Kamaruzaman Syed Ali, Reza Adityas Trisnadi, Asmuddin Asmuddin, Danarstuti Utami

“…This implies that there exists a substantial impact resulting from the utilization of online learning-based large ball game educational media on students' learning outcomes. …”
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Digital propaganda and disinformation generated via artificial intelligence:The Israel/ Palestine conflict and the fall of Bashar al-Assad in Syria case studies by Kazić Tanja

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SSFAN: A Compact and Efficient Spectral-Spatial Feature Extraction and Attention-Based Neural Network for Hyperspectral Image Classification by Chunyang Wang, Chao Zhan, Bibo Lu, Wei Yang, Yingjie Zhang, Gaige Wang, Zongze Zhao

“…Additionally, it requires less training and testing time compared to other state-of-the-art deep learning methods.…”
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On the machine learning algorithm combined evolutionary optimization to understand different tool designs’ wear mechanisms and other machinability metrics during dry turning of D2... by Muhammad Sana, Muhammad Umar Farooq, Sana Hassan, Anamta Khan

“…However, understanding the interactions of these designs with machining parameter selection considered time-taking process through various trial and error experiments. In this study, three-step novel modelling approach for optimal prediction of dry turning parameters is proposed. …”
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Strengthening nutrition routine data using institutionalized health management information systems for decision making: analysis of best practices and lessons learned from implemen... by Ousmane Ouedraogo, Mahamadi Tassembedo, Assane Ouangare, Estelle Bambara, Paton Guillaume Paré, Boro Gosso, Fulbert Ilboudo, Céline Zongo, Rodrigue Kouamé, Mediatrice Kiburente, Saidou Diallo, Barbara Baille, Justine Marie Francoise Briaux, John Ntambi, Norah Stoops, Simeon Nanama

“…Results The results of the study show the best practices and progress identified: (i) the integration of new routine data elements and nutrition indicators into District Health Information Software (DHIS2), which filled the data gap for adequate monitoring of the nutrition program; (ii) the design and use of the nutrition indicator dashboard; (iii) data validation and performance review sessions which have improved the quality and use of routine data in decision-making; and (iv) decentralization of data entry of monthly activity reports of health facilities. Lessons learned included: (i) conducting a small-scale phase to test the indicators is an important step to take before national scale-up of the indicators; (ii) a participatory approach involving all actors at different levels is important; (iii) advocacy is important to integrate prevention indicators into health facilities information systems in a more curative-oriented health system; (iv) the decentralized entry of data is a best practice that improves data quality in terms of timeliness, completeness, and internal consistency. …”
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Listen, look, link and learn: a stepwise approach to use narrative quality data within resident-family-nursing staff triads in nursing homes for quality improvements by Jos M G A Schols, Jan P H Hamers, Katya Y J Sion, Johanna E R Rutten, Erica de Vries, Sandra M G Zwakhalen, Gaby Odekerken-Schröder, Hilde Verbeek

“…Data analysis consisted of coding positive/negative valences in each transcript.Findings A stepwise approach can support the use of narrative quality data consisting of four steps: (1) perform and transcribe the conversations (listen); (2) calculate a valence sore, defined as the mean %-positive within a triad (look); (3) calculate an agreement score, defined as the level of agreement between resident-family-nursing staff (link); and (4) plot scores into a graph for interpretation and learning purposes with agreement score (x-axis) and valence score (y-axis) (learn).Conclusions Narrative quality data can be interpreted as a valence and agreement score. …”
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Integration of Explainable Artificial Intelligence into Hybrid Long Short-Term Memory and Adaptive Kalman Filter for Sulfur Dioxide (SO₂) Prediction in Kimberley, South... by Israel Edem Agbehadji, Ibidun Christiana Obagbuwa

“…Though several machine learning and deep learning models are used to analyze air pollutants, model interpretability is a challenge. …”
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Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female b... by Ricardo Gonzalez, Peyman Nejat, Ashirbani Saha, Clinton J.V. Campbell, Andrew P. Norgan, Cynthia Lokker

“…Numerous machine learning (ML) models have been developed for breast cancer using various types of data. …”
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