Integrating machine learning-based classification and regression models for solvent regeneration prediction in post-combustion carbon capture: An absorption-based case by Farzin Hosseinifard, Mostafa Setak, Majid Amidpour

“…The first sub-model applies classification techniques Logistic Regression, AdaBoost, Support Vector Classifier, Gradient Boosting, Naive Bayes, Decision Tree, Random Forest, and K-Nearest Neighbors to determine the most suitable solvent based on variables such as pressure, temperature, and concentration. …”
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Determining the optimal generalization operators for building footprints using an improved graph neural network model by Xinyu Niu, Haizhong Qian, Xiao Wang, Limin Xie, Longfei Cui

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A Comparative Performance of SMOTE, ADASYN and Random Oversampling in Machine Learning Models on Prostate Cancer Dataset by Aditya Herdiansyah Putra, Abu Salam

“…Class imbalance in medical datasets, including prostate cancer, can affect the performance of machine learning models in detecting minority cases. This study compares three oversampling techniques - SMOTE, ADASYN, and Random Oversampling - to address data imbalance in prostate cancer classification. …”
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An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network by R. Karthik, Armaano Ajay, Anshika Jhalani, Kruthik Ballari, Suganthi K

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HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson’s Disease Classification and Severity Prediction by Anitha Rani Palakayala, P. Kuppusamy, D. Kothandaraman, Gunakala Archana, Jaideep Gera

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A Multi-Modal Approach Using a Hybrid Vision Transformer and Temporal Fusion Transformer Model for Stock Price Movement Classification by Ibanga Kpereobong Friday, Sarada Prasanna Pati, Debahuti Mishra

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M5 Soft Computing Techniques for Assessment of Soil Liquefaction by Abu Sayed, Md Rahman

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Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification by Muhammad Waqar, Zeshan Aslam Khan, Shanzey Tariq Khawaja, Naveed Ishtiaq Chaudhary, Saadia Khan, Khalid Mehmood Cheema, Muhammad Farhan Khan, Syed Sohail Ahmed, Muhammad Asif Zahoor Raja

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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

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Trade-Space Exploration With Data Preprocessing and Machine Learning for Satellite Anomalies Reliability Classification by Abdul Mutholib, Nadirah Abdul Rahim, Teddy Surya Gunawan, Mira Kartiwi

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Realtime Monitoring of Animal Behavior Using Deep Learning Models by Romesa Rao, Salman Qadri, Rao Kashif

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A warning model for predicting patient admissions to the intensive care unit (ICU) following surgery by Li Li, Hongye He, Linjun Xiang, Yongxiang Wang

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An example of the application of artificial intelligence models in human resources processes by Mustafa Kemal Aydın, Berk Küçük, Selim Sürücü

“…In the second stage, the resumes of the applicants are analyzed using three different deep learning models such as CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit), and LSTM (Long Short-Term Memory) for classification purposes. …”
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IT Diagnostics of Parkinson’s Disease Based on the Analysis of Voice Markers and Machine Learning by U. A. Vishniakou, Xia YiWei

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Balanced Multi-Class Network Intrusion Detection Using Machine Learning by Faraz Ahmad Khan, Asghar Ali Shah, Nizal Alshammry, Saifullah Saif, Wasim Khan, Muhammad Osama Malik, Zahid Ullah

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Toward a fair, gender-debiased classifier for the diagnosis of attention deficit/hyperactivity disorder- a Machine-Learning based classification study by Susanne Neufang, Feifei Li, Atae Akhrif, Oya D. Beyan

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Development and validation of machine learning models for predicting blastocyst yield in IVF cycles by Wen-jie Huo, Fei Peng, Song Quan, Xiao-cong Wang

“…We then stratified predictions and actual yields into three categories (0, 1–2, and ≥ 3 blastocysts) to evaluate the model’s discriminative performance. …”
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A Unified Framework for Alzheimer’s Disease Knowledge Graphs: Architectures, Principles, and Clinical Translation by Jovana Dobreva, Monika Simjanoska Misheva, Kostadin Mishev, Dimitar Trajanov, Igor Mishkovski

“…The framework accommodates a variety of applications, including drug repurposing, patient stratification for precision medicine, disease progression modeling, and clinical decision support. Our system, with a decision tree structured and pipeline layered architecture, offers research precise directions on how to use knowledge graphs in AD research by aligning methodological choice decisions with respective data availability and application goals. …”
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Optimizing Jatropha curcas bioenergy plantations in Pakistan: A geospatial suitability analysis using advanced spatial modeling by Faisal Khalid, Sami Ullah, Sangam Khalil, Adnan Yousaf, Muhammad Shafique, Muhammad Tayyab Khan, Fariha Rehman, Nauman Ahmad, Khalil Ur Rahman, Majid Hussain

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Enhanced Feature Selection via Hierarchical Concept Modeling by Jarunee Saelee, Patsita Wetchapram, Apirat Wanichsombat, Arthit Intarasit, Jirapond Muangprathub, Laor Boongasame, Boonyarit Choopradit

“…The presented methods are evaluated based on all learned attributes with 10 datasets from the UCI Machine Learning Repository by using three classification algorithms, namely decision trees, support vector machines (SVM), and artificial neural networks (ANN). …”
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