Data-driven approach for identifying the factors related to debt collector performance by Keerthana Sivamayilvelan, Elakkiya Rajasekar, Santhi Balachandran, Ketan Kotecha, Subramaniyaswamy Vairavasundaram

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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…However, its specific implications in lung squamous cell carcinoma (LUSC) remain unclear.MethodsWe used numerous datasets encompassing bulk and single-cell transcriptome, genome, intratumor microbiome, and digital pathome to systematically investigate the LM patterns in LUSC. Multiple machine learning algorithms were used to generate the LUSC classification. …”
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An Analysis of Consumer Purchase Behavior Following Cart Addition in E-Commerce Utilizing Explainable Artificial Intelligence by Ramazan Esmeli, Aytac Gokce

“…The comprehensive experimental results obtained from two datasets and eight models demonstrate that machine learning algorithms can achieve an F1 score of 89% in predicting purchase behavior following cart additions. …”
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Urban heat island classification through alternative normalized difference vegetation index by N. Chanpichaigosol, C. Chaichana, D. Rinchumphu

“…The findings contribute to a deeper understanding of urban heat island effects and provide a basis for enhancing machine Learning models and urban planning frameworks. …”
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Pseudo-Labeling and Time-Series Data Analysis Model for Device Status Diagnostics in Smart Agriculture by Minwoo Jung, Dae-Young Kim

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Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

“…In order to efficiently evaluate the quality of rock blasting in mines, this paper developed a blasting effect image analysis and calculation model and recognition algorithm based on the established machine learning database, and carried out recognition and analysis work on the half-hole rate and rock blasting fragmentation of pre-splitting blasting. …”
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Key Vital Signs Monitor Based on MIMO Radar by Michael Gottinger, Nicola Notari, Samuel Dutler, Samuel Kranz, Robin Vetsch, Tindaro Pittorino, Christoph Würsch, Guido Piai

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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides by Nitin Kumar Chauhan, Krishna Singh, Amit Kumar, Ashutosh Mishra, Sachin Kumar Gupta, Shubham Mahajan, Seifedine Kadry, Jungeun Kim

“…Abstract Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) methods, specifically convolutional neural networks (CNNs), are extremely accurate at identifying malignant lesions. …”
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies by Zipei Song, Yuheng Wang, Miaolin Zhu, Pengpeng Zhang, Zhihua Li, Xin Geng, Xincen Cao, Jianan Zheng, Jianwei Tang, Liang Chen

“…Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. …”
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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

“…The research involved collecting conversational speech samples from pregnant women attending a high-risk pregnancy outpatient service, employing smartphones to capture naturalistic speech in everyday contexts. Machine learning algorithms were utilized combined with different audio feature sets to analyze these recordings in conjunction with PHQ-4 questionnaire scores. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…This study aims to develop artificial intelligence algorithms based on gait analysis, integrating sensor and computer vision (CV) data, to detect sarcopenia and CD. …”
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Towards ML Models’ Recommendations by Lara Kallab, Elio Mansour, Richard Chbeir

“…A prominent way to achieve this is machine learning (ML), which optimizes system performance by employing learning algorithms to create models based on data and its inherent patterns. …”
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Geoinformatics-based prioritisation of natural resources rich regions at disaggregated levels for sustainable management by T. V. Ramachandra, Paras Negi

“…Landscape dynamics is assessed by classifying temporal remote sensing data using the supervised machine learning (ML) technique based on the Random Forest (RF) algorithm. …”
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Integration of Microarray Data and Single-Cell Sequencing Analysis to Explore Key Genes Associated with Macrophage Infiltration in Heart Failure by Rao J, Wang X, Wang Z

“…Additionally, we employed four integrated machine learning algorithms to identify macrophage-related genes with diagnostic value, and in vivo validation was performed. …”
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Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations by Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene

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The role of epigenetic regulation in pancreatic ductal adenocarcinoma progression and drug response: an integrative genomic and pharmacological prognostic prediction model by Kang Fu, Junzhe Su, Yiming Zhou, Xiaotong Chen, Xiao Hu

“…Weighted gene co-expression network analysis (WGCNA) identified key epigenetic modules. A machine learning-based prognostic model was constructed using multiple algorithms, including Lasso and Random Survival Forest. …”
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Leveraging environmental microbial indicators in wastewater for data-driven disease diagnostics by Gayatri Gogoi, Gayatri Gogoi, Sarangthem Dinamani Singh, Sarangthem Dinamani Singh, Devpratim Koch, Devpratim Koch, Emon Kalyan, Rashmi Rani Boro, Aradhana Devi, Hridoy Jyoti Mahanta, Hridoy Jyoti Mahanta, Pankaj Bharali, Pankaj Bharali

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Smartphone sensor-based depression detection in campus environments: a proof-of-concept study with small-sample behavioral analysis by Yichen Bai, Yueze Liu, Yang Zhang, Amr Tolba

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Breast Cancer Diagnosis Using Bagging Decision Trees with Improved Feature Selection by Deepak Dudeja, Ajit Noonia, S. Lavanya, Vandana Sharma, Varun Kumar, Sumaiya Rehan, R. Ramkumar

“…Machine learning is a science of computer algorithms that enable systems to automatically learn actions and adjust them without explicit programming and improve from experience using pattern recognition. …”
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