Komparasi Data Mining Naive Bayes dan Neural Network memprediksi Masa Studi Mahasiswa S1 by Azahari Azahari, Yulindawati Yulindawati, Dewi Rosita, Syamsuddin Mallala

“…By using the data mining algorithm Naive bayes and neural network, the student graduation in STMIK Widya Cipta Dharma (WiCiDa) can be predicted. …”
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Neural Network Approaches for Distributional Shifts in Environmental Sensors by Tobias Sukianto, Sebastian A. Schober, Cecilia Carbonelli, Simon Mittermaier, Robert Wille

“…Due to the distributional shift between the training and operational environment induced by sensor ageing and drift processes, the algorithms that predict air quality suffer from performance degradation during the products’ lifetime. …”
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Artificial intelligence models in corporate financial and accounting processes: systematic literature review by Deivi David Fuentes Doria, Aníbal Toscano Hernández, Johana Elisa Fajardo Pereira

“…The results suggest that supervised models are the most applied in the accounting and financial field, while the algorithms that have been most used are decision trees, support vector machines, random forests, neural networks, and logistic regressions, employed in specific areas of financial fraud, stock market predictions, and cash flow. …”
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Differing Effects of Alcohol Use on Epigenetic and Brain Age in Adult Children of Parents with Alcohol Use Disorder by Jamie L. Scholl, Kami Pearson, Kelene A. Fercho, Austin J. Van Asselt, Noah A. Kallsen, Erik. A. Ehli, Kari N. Potter, Kathleen A. Brown-Rice, Gina L. Forster, Lee A. Baugh

“…We examined structural brain differences and applied machine learning algorithms to predict biological brain and DNA methylation ages to investigate differences and determine any accelerated aging between these groups. …”
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Modeling of erosion processes in open channels by M. R. Magomedova

“…A technique has been developed for predicting the general erosion of riverbeds and canals, composed of homogeneous and heterogeneous non-cohesive soils. …”
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Short-Term Traffic Flow Forecasting Model Based on GA-TCN by Rongji Zhang, Feng Sun, Ziwen Song, Xiaolin Wang, Yingcui Du, Shulong Dong

“…The prediction error was considered as the fitness value and the genetic algorithm was used to optimize the filters, kernel size, batch size, and dilations hyperparameters of the temporal convolutional neural network to determine the optimal fitness prediction model. …”
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Calibration Transfer of Near-Infrared Spectroscopic Model for Soluble Solid Content Predication of Apples by the Combined Use of Direct Standardization and Piecewise Direct Standar... by CHENG Ye, HUANG Haoran, WANG Ying, XIONG Zhixin

“…The results indicated that compared with DS and PDS, the combined algorithm not only significantly improved the prediction performance of the model for the slave instrument, but also mitigated the artifacts caused by PDS. …”
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Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research by Parveen Kumar, Benu Chaudhary, Preeti Arya, Rupali Chauhan, Sushma Devi, Punit B. Parejiya, Madan Mohan Gupta

“…Seasonal flu, Ebola, Zika, COVID-19, tuberculosis, and outbreak predictions were made using deep computation and artificial intelligence. …”
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Enhanced MCDM Based on the TOPSIS Technique and Aggregation Operators Under the Bipolar pqr-Spherical Fuzzy Environment: An Application in Firm Supplier Selection by Zanyar A. Ameen, Hariwan Fadhil M. Salih, Amlak I. Alajlan, Ramadhan A. Mohammed, Baravan A. Asaad

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Identification and Evaluation of Lipocalin-2 in Sepsis-Associated Encephalopathy via Machine Learning Approaches by Hu J, Chen Z, Wang J, Xu A, Sun J, Xiao W, Yang M

“…Subsequently, neuroinflammation-related genes were obtained to construct a neuroinflammation-related signature. The AddModuleScore algorithm was used to calculate neuroinflammation scores for each cell subpopulation, whereas the CellCall algorithm was used to assess the crosstalk between neutrophils and other cell subpopulations. …”
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Comparison of Raman spectroscopy with mass spectrometry for sequence typing of Acinetobacter baumannii strains: a single-center study by Suling Liu, Ni Zhang, Jiawei Tang, Chong Chen, Weisha Wang, Jingfang Zhou, Long Ye, Xiaoli Chen, ZhengKang Li, Liang Wang

“…This study developed a novel approach, combining surface-enhanced Raman spectroscopy (SERS) with machine-learning (ML) algorithms, to construct predictive models for A. baumannii sequence typing based on SERS spectra. …”
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Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…The future of AI in venous diagnostics is promising, and several areas of development were noted, including AI algorithms embedding directly into ultrasound devices to provide instantaneous diagnostic insights during patient evaluations; combining AI-processed Doppler data with other imaging modalities, such as computed tomography or MRI, for comprehensive assessments; AI usage in order to predict disease progression and tailor treatment strategies based on individual patient profiles; and constructing large-scale, multicenter datasets to improve the robustness and generalizability of AI algorithms.…”
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Intelligent CO2 Monitoring for Diagnosis of Sleep Apnea Using Neural Cryptography Techniques by Manar Ahmed Hamza, Maha M. Althobaiti, Ola Abdelgney Omer Ali, Souad Larabi-Marie-Sainte, Majdy M. Eltahir, Anwer Mustafa Hilal, Mesfer Al Duhayyim, Ishfaq Yaseen

“…The key advantage of the proposed work shows excellent performance in the prediction of adsorbing carbon and accuracy. The accuracy of the GEP-KNN algorithm with different K values produced the highest accuracy at K=9 and k=10 of 95.12% and 95.67%; the lowest accuracy is K=1 of 65.34%.…”
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A photogrammetric approach to the estimation of distance to animals in camera trap images by B. Mirka, C.D. Lippitt, G.M. Harris, R. Converse, M. Gurule, S.E. Sesnie, M.J. Butler, D.R. Stewart, Z. Rossman

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Integrative analysis of crotonylation-associated genes reveals prognostic and therapeutic targets in gliomas by Bowen Yin, Bowen Yin, Zhuoyang Fan, Panpan Yu, Panpan Yu, Jin Li, Jin Li, Yilin Wang, Yilin Wang, Minfeng Shu, Minfeng Shu

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Agenda setting for health equity assessment through the lenses of social determinants of health using machine learning approach: a framework and preliminary pilot study by Maryam Ramezani, Mohammadreza Mobinizadeh, Ahad Bakhtiari, Hamid R. Rabiee, Maryam Ramezani, Hakimeh Mostafavi, Alireza Olyaeemanesh, Ali Akbar Fazaeli, Alireza Atashi, Saharnaz Sazgarnejad, Efat Mohamadi, Amirhossein Takian

“…These models highlighted the importance of features like current health expenditure, domestic general government health expenditure, and GDP in predicting life expectancy. Conclusion The findings underscore the significance of employing innovative methods like CRISP-ML(Q) and ML algorithms to enhance health equity. …”
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Utilising artificial intelligence in prehospital emergency care systems in low- and middle-income countries: a scoping review by Odhran Mallon, Odhran Mallon, Odhran Mallon, Freddy Lippert, Freddy Lippert, Willem Stassen, Marcus Eng Hock Ong, Caitlin Dolkart, Caitlin Dolkart, Thomas Krafft, Eva Pilot

“…Overall, machine learning algorithms outperformed other comparator methods when they were used in all but two studies.DiscussionLimitations included only analysing articles published in English. …”
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Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network by Zehua Li, Zehua Li, Yihui Pan, Xu Ma, Yongjun Lin, Xicheng Wang, Hongwei Li

“…Compared to the advanced object detection algorithms such as Faster-RCNN, SSD, YOLOv4, YOLOv5s YOLOv7-tiny, and YOLOv10s, the mAP of the new network increased by 5.2%, 7.8%, 4.9%, 2.8% 2.9%, and 3.3%, respectively. …”
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Development of over 30-years of high spatiotemporal resolution air pollution models and surfaces for California by Jason G. Su, Eahsan Shahriary, Emma Sage, John Jacobsen, Katherine Park, Arash Mohegh

“…These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. …”
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Remote Sensing Time Series Analysis: A Review of Data and Applications by Yingchun Fu, Zhe Zhu, Liangyun Liu, Wenfeng Zhan, Tao He, Huanfeng Shen, Jun Zhao, Yongxue Liu, Hongsheng Zhang, Zihan Liu, Yufei Xue, Zurui Ao

“…., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. …”
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