Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This work assists researchers in selecting the most effective bio-inspired algorithm for disease categorization, prediction, and the analysis of high-dimensional biomedical data.…”
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Vers les analyses algorithmiques de l'espace et des territoires by Claire Bailly, Jean Magerand

“…Big data, data mining and machine learning are undergoing unprecedented development. …”
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Reliability Assessment of PM2.5 Concentration Monitoring Data: A Case Study of China by Hongyan Duan, Wenfu Yue, Weidong Li

“…By using Benford’s Law, robust regression analysis, and various machine learning methods, such as Gradient Boosting Trees and Random Forests, the overall reliability of China’s PM2.5 monitoring data is high. …”
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Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

“…Abstract Missing data in electronic health records (EHRs) poses a significant challenge for analysis. …”
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Masked pre-training of transformers for histology image analysis by Shuai Jiang, Liesbeth Hondelink, Arief A. Suriawinata, Saeed Hassanpour

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Machine Learning and Deep Learning Approaches for Fake News Detection: A Systematic Review of Techniques, Challenges, and Advancements by Omar Bashaddadh, Nazlia Omar, Masnizah Mohd, Mohd Nor Akmal Khalid

“…This review also underscores the limited adoption of few-shot and zero-shot learning techniques, highlighting a promising direction for future research on handling emerging misinformation using minimal training data. …”
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An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation by Sadia Sultana Chowa, Md Rahad Islam Bhuiyan, Mst. Sazia Tahosin, Asif Karim, Sidratul Montaha, Md. Mehedi Hassan, Mohd Asif Shah, Sami Azam

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Incremental capacity analysis of battery under dynamic load conditionsData downloaded from the site: . by Urvashi Saini, Sindhuja Renganathan

“…This method not only provides labeled SOH values but also extracts health features that can be used for data-driven prediction of capacity or SOH. • Incremental capacity analysis (ICA) method has been presented to be used with electric vehicle (EV) battery data. • The approach to extract health features from a EV battery using ICA method as a function of age of the battery has been presented which can be used along with a machine learning or deep learning model. • State of health has been calculated for a vehicle battery using the proposed method.…”
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Prognostic Survival Analysis for AD Diagnosis and Progression Using MRI Data: An AI-Based Approach by T. Deenadayalan, S. P. Shantharajah

“…This study proposes a novel AI framework combining EfficientNetB0, a state-of-the-art deep learning model, with dual attention mechanisms for robust feature extraction and survival analysis using the Alzheimer’s MRI dataset hosted on the Kaggle platform. …”
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Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages by Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad

“…Additionally, the proposed model outperformed other transformer-based models, as well as deep learning and machine learning algorithms in sentiment extraction from code-mixed data. …”
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Interpreting Global Terrestrial Water Storage Dynamics and Drivers with Explainable Deep Learning by Haijun Huang, Xitian Cai, Lu Li, Xiaolu Wu, Zichun Zhao, Xuezhi Tan

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Comparative Analysis of Multi-Resolution Remote Sensing Data for Accurate Road Segmentation in Urban Environments by M. R. Çevikalp, B. Mutlu, M. Yanalak, N. Musaoğlu

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A Lightweight Transformer-Based Spatiotemporal Analysis Prediction Algorithm for High-Dimensional Meteorological Data by Yinghao Tan, Junfeng Wu, Yihang Liu, Shiyu Shen, Xia Xu, Bin Pan

“…This paper presents the spatiotemporal analysis fitting prediction algorithm (SA-Fit), an approximation algorithm for regional high-dimensional meteorological data prediction. …”
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A comprehensive survey and comparative analysis of time series data augmentation in medical wearable computing. by Md Abid Hasan, Frédéric Li, Philip Gouverneur, Artur Piet, Marcin Grzegorzek

“…This proliferation has resulted in a notable increase in the availability of Time Series (TS) data characterizing behavioral or physiological information from the patient, leading to initiatives toward leveraging machine learning and data analysis techniques. …”
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Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis. by Jessica L Nielson, Shelly R Cooper, John K Yue, Marco D Sorani, Tomoo Inoue, Esther L Yuh, Pratik Mukherjee, Tanya C Petrossian, Jesse Paquette, Pek Y Lum, Gunnar E Carlsson, Mary J Vassar, Hester F Lingsma, Wayne A Gordon, Alex B Valadka, David O Okonkwo, Geoffrey T Manley, Adam R Ferguson, TRACK-TBI Investigators

“…Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. …”
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Data Analysis and Optimization Strategies for Delivery Operations in a Shenyang-Based Convenience Store Network by Yuan Feier

“…This study focuses on optimizing delivery operations in a Shenyang-based convenience store network by analyzing delivery time, cost, order distribution, and external factors such as weather and traffic. Using Python-based data analysis, inefficiencies in delivery times, rising costs due to fuel and labor, and uneven order distribution across routes were identified Visualizations are plotted to highlight the impact of longer routes on time and cost and evaluated external influences like traffic and weather. …”
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Intelligent data analysis in edge computing with large language models: applications, challenges, and future directions by Xuanzheng Wang, Zhipeng Xu, Xingfei Sui

“…Simultaneously, large language models (LLMs) such as GPT-4 and BERT have showcased impressive capabilities in data analysis, natural language processing, and decision-making. …”
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Improving Statistical Analysis in Supporting Big Data Era for SMA Negeri 1 Krembung Teachers by Nur Silviyah Rahmi

“…Consequently, it can be concluded that repeating training activities is essential to enhance statistical and data science-based analysis skills in the big data era and to provide a deeper understanding of Classroom Action Research.…”
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Core collaApse Supernovae parameTers estimatOR a novel software for data analysis by Simongini Andrea, Ragosta Fabio, Piranomonte Silvia, Di Palma Irene

“…In this poster we presented the novel open-access software for core collapse supernovae optical analysis: CASTOR. This software enables the reconstruction of synthetic light curves and spectra via a machine learning technique that allows to retrieve the complete parameter map of a supernova having as only input the multi-band photometry data. …”
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MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles by Salvatore Milite, Giulio Caravagna, Andrea Sottoriva

“…Here, we introduce a framework that combines archetypal analysis, an approach grounded in biological principles, with deep learning. …”
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