Localization of Capsule Endoscope in Alimentary Tract by Computer-Aided Analysis of Endoscopic Images by Ruiyao Zhang, Boyuan Peng, Yiyang Liu, Xinkai Liu, Jie Huang, Kohei Suzuki, Yuki Nakajima, Daiki Nemoto, Kazutomo Togashi, Xin Zhu

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A Comprehensive Review on Document Image Binarization by Bilal Bataineh, Mohamed Tounsi, Nuha Zamzami, Jehan Janbi, Waleed Abdel Karim Abu-ain, Tarik AbuAin, Shaima Elnazer

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Gene2role: a role-based gene embedding method for comparative analysis of signed gene regulatory networks by Xin Zeng, Shu Liu, Bowen Liu, Weihang Zhang, Wanzhe Xu, Fujio Toriumi, Kenta Nakai

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Can synthetic data be a proxy for real clinical trial data? A validation study by Monica Parry, Karolina Kublickiene, Valeria Raparelli, Peter Klimek, Alexandra Kautzky-Willer, Louise Pilote, Michal Abrahamowicz, Colleen M. Norris, Maria Trinidad Herrero, Khaled El Emam, Ruth Sapir-Pichhadze, Simon Bacon, Jennifer Fishman, Zahra Azizi, Chaoyi Zheng, Lucy Mosquera, Karin Humphries, Khaled El Emam

“…This challenge can potentially be addressed using synthetic data.Setting Replication of a published stage III colon cancer trial secondary analysis using synthetic data generated by a machine learning method.Participants There were 1543 patients in the control arm that were included in our analysis.Primary and secondary outcome measures Analyses from a study published on the real dataset were replicated on synthetic data to investigate the relationship between bowel obstruction and event-free survival. …”
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Mid-infrared spectra of dried and roasted cocoa (Theobroma cacao L.): A dataset for machine learning-based classification of cocoa varieties and prediction of theobromine and caffe... by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…This dataset provides a basis for further research, enabling the integration of mid-infrared spectral data with HPLC (as a standard) to fine-tune machine learning and deep learning models that could be used to simultaneously predict the theobromine and caffeine content, as well as cocoa variety in both dried and roasted cocoa samples using a non-destructive approach based on spectral data. …”
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DeFiSentinel: AI-Enhanced Decentralized Finance Architecture With Advanced Cryptographic Smart Contracts for Data Integrity and Threat Resilience by Seyed Mani Rahnama

“…However, it introduces security vulnerabilities, fraud risks, and data integrity challenges that traditional financial frameworks fail to address. …”
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Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine l... by Ta-Chien Chan, Jiunn-Horng Kang, Tian-Shin Yeh, Nguyen Thanh Nhu, Jer-Hwa Chang, Yu-Tien Tzeng, Chia-Chieh Wu, Carlos Lam

“…Given that the 14-day readmission rate is considered a healthcare quality indicator, this study is the first to develop survival machine learning (ML) models using emergency department (ED) data to predict 14-day readmission risk following pneumonia-related admissions.Design A retrospective multicentre cohort study.Setting This study used the Taipei Medical University Clinical Research Database, including data from patients at three affiliated hospitals.Participants 11 989 hospital admissions for pneumonia among patients aged ≥45 years admitted from 2014 to 2021.Primary and secondary outcome measures The dataset was randomly split into training (80%), validation (10%) and independent test (10%) sets. …”
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Statistical learning to identify and characterise neurodevelopmental outcomes at 2 years in babies born preterm: model development and validation using population-level data from E... by Sadia Haider, Athanasios Tsanas, G. David Batty, Rebecca M. Reynolds, Heather C. Whalley, Simon R. Cox, Riccardo E. Marioni, Cheryl Battersby, James P. Boardman

“…Methods: Latent class analysis (LCA) was used to derive transdomain clusters from parent-reported visual, auditory, neuromotor, and communication impairments in preterm-born children at two years corrected age using the UK National Neonatal Research Database data (N = 27,261). …”
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The performance of the LSTM-based code generated by Large Language Models (LLMs) in forecasting time series data by Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin

“…As an intriguing case is the goodness of the machine and deep learning models generated by these LLMs in conducting automated scientific data analysis, where a data analyst may not have enough expertise in manually coding and optimizing complex deep learning models and codes and thus may opt to leverage LLMs to generate the required models. …”
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Characterization and Automated Classification of Underwater Acoustic Environments in the Western Black Sea Using Machine Learning Techniques by Maria Emanuela Mihailov

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Integrating bioinformatics and machine learning to investigate the mechanisms by which three major respiratory infectious diseases exacerbate heart failure by Yiding Yu, Quancheng Han, Juan Zhang, Jingle Shi, Huajing Yuan, Yitao Xue, Yan Li

“…By performing differential expression analysis on GEO database data, we found 51 common molecules of three respiratory diseases. …”
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Predicting the mechanical performance of industrial waste incorporated sustainable concrete using hybrid machine learning modeling and parametric analyses by Md. Alhaz Uddin, Md. Habibur Rahman Sobuz, Md. Kawsarul Islam Kabbo, Md. Kanan Chowdhury Tilak, Ratan Lal, Md. Selim Reza, Fahad Alsharari, Mohamed AbdelMongy, Masuk Abdullah

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Encoding Behavior Commonalities In Global Stock Market Indexes: Unsupervised Machine Learning Approach by Suresh Vidya, Kolluru Mythili, Ubaidullah Vaheed

“…Daily time series data for global stock indices from 2002, to 2023, is analyzed. …”
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ImmuProgML: machine learning-based dissection of cancer-immune dynamics during tumor progression to improve immunotherapy by Hanxiao Zhou, Lan Mei, Qianyi Lu, Yakun Zhang, Yue Sun, Caiyu Zhang, Han Jiang, Jiajun Zhou, Xia Li, Yunpeng Zhang, Shangwei Ning

“…Methods We developed ImmuProgML framework by integrating multi-omics data and dynamic network biomarker (DNB) analysis to identify key pathways and critical stages in cancer progression, tested in melanoma and non-small cell lung cancer (NSCLC). …”
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Voices from The Classroom : Teachers’ and Students’ Perceptions of Using SPS-Based Worksheets to Promote HOTS in Science Learning (A Needs Analysis) by Syarifah Widia, Evendi Evendi, A. Halim

“…This study aims to analyze the needs for developing Student Worksheets that support Higher Order Thinking Skills (HOTS) and Science Process Skills (SPS) in science learning. A descriptive qualitative approach was employed in this study, where data were collected from 56 students and 3 science teachers across two schools in Banda Aceh, which were purposefully selected to examine the implementation of SPS-based worksheets in school located in the both urban and rural setting using structured questionnaires. …”
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Novel machine‐learning bioinformatics reveal distinct metabolic alterations for enhanced colorectal cancer diagnosis and monitoring by Rui Xu, Hyein Jung, Fouad Choueiry, Shiqi Zhang, Rachel Pearlman, Heather Hampel, Ning Jin, Jieli Li, Jiangjiang Zhu

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An optimized public opinion communication system in social media networks based on K-means cluster analysis by Mingchao Qi, JunQiang Zhao, Yan Feng

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Computational analysis of DEHP’s oncogenic role in colorectal cancer by Zhou Zhu, Jian Qin, Chungang He, Shuangyou Wang, Yaolin Lu, Shuai Wang, Xiaogang Zhong

“…SHAP analysis and ssGSEA were employed to evaluate gene importance and immune cell infiltration, respectively. …”
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A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students by Flórián Gubics, Ádám Nagy, József Dombi, Antónia Pálfi, Zoltán Szabó, Zsolt János Viharos, Anh Tuan Hoang, Vilmos Bilicki, István Szendi

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Article RETRACTED due to manipulation by the authors The Hybrid Learning System With Project Based Learning: Can It Increase Creative Thinking Skill and Learning Motivation in Phys... by Rifqi Festiawan, Eko Sumanto, Ayu Rizky Febriani, Asep Angga Permadi, Z. Arifin, Andri Wahyu Utomo, Wildan Alfia Nugroho, Kukuh Wahyudin Pratama

“…The data analysis used was the data normality test, data homogeneity test, paired t-test and independent t-test. …”
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