Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

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Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders by Hui Yang, Walid Aydi, Nisreen Innab, Mohamed E. Ghoneim, Massimiliano Ferrara

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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

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Deep Classification of Algarrobo Trees in Seasonally Dry Forests of Peru Using Aerial Imagery by Wilson Castro, Himer Avila-George, William Nauray, Roenfi Guerra, Jorge Rodriguez, Jorge Castro, Miguel de-la-Torre

“…As a proof of concept, three state-of-the-art approaches were evaluated in selected zones of interest, and a new application-specific architecture called AlgarroboNet was proposed for efficient classification of plus algarrobo trees. …”
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Skin Lesion Diagnosis Through Deep Learning and Hybrid Texture Feature Augmentation by Irpan Adiputra Pardosi, Roni Yunis, Arwin Halim

“…The framework integrates handcrafted features with Convolutional Neural Networks (CNNs) to enhance classification accuracy. Key contributions include: Automated parameter tuning for GLCM and LBP using grid search and cross-validation; A hybrid model combining EfficientNet-B3 with full handcrafted features; Comprehensive evaluation on the ISIC 2023 dataset (10,015 images). …”
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Deep learning-based cough classification using application-recorded sounds: a transfer learning approach with VGGish by Sanghoon Han, Yu-rim Lee, Ji-ho Lee, JinHee Jeon, Choongki Min, Kyungnam Kim, Donghoon Kim, Myung Pyo Kim, Young Mi Park, Uiri An, Kyoung Min Moon

“…Results Experimental evaluations demonstrated that the cough detection model achieved an average accuracy of 0.9883, while the cough classification model attained accuracies of 0.8417, 0.8629, and 0.8662 among dataset1, 2, and 3. …”
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Development of a CNN-based decision support system for lung disease diagnosis using chest radiographs by B. T. Magar, M. A. Rahman, P. K. Saha, M. Ahmad, M. A. Rashid, H. Higa

“…Extensive testing under three different data distribution conditions demonstrated the model’s superior performance, achieving an average accuracy of 95.7%, precision of 95.3%, recall of 95.3%, and an F1-score of 95.3% for multi-class classification. …”
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Deepfake Detection Using Spatio-Temporal-Structural Anomaly Learning and Fuzzy System-Based Decision Fusion by Brindha Subburaj, R. Ragavendra

“…A novel three input and one output Fuzzy Inference System is designed for decision fusion combining the detection results of all three classifier models to make decision on video being a fake. …”
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Discovering the key symptoms for identifying patterns in functional dyspepsia patients: A doctor's decision and machine learning by Da-Eun Yoon, Heeyoung Moon, In-Seon Lee, Younbyoung Chae

“…Implicit importance was assessed by feature importance from the random forest classification models, which classify the three pattern for general differentiation and perform binary classification for specific types. …”
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Classification of products based on the uncertainty of supply chain demand: a case study of wineries in Chile by Armando Camino, Juan Pablo Vargas

“…Using a case study of three Chilean wineries located in the Central Valley, we compare the traditional ABC classification – commonly used in ERP systems – with a quantitative model that incorporates demand variability. …”
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CFP-SwinT: building damage classification during floods using cross fusion pyramid Swin-T by Chuyi Wu, Zeyu Wang, Junshi Xia, Feng Zhang

“…Timely building damage detection is crucial in disaster decision-making. Unlike existing studies using sub-meter resolution images, we employ stable, mid-high resolution (1–3 meters) remote sensing data to develop building flood damage classification methods for quick disaster response. …”
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Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina by Džana Bašić-Čičak, Jasminka Hasić Telalović, Lejla Pašić

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Efficient Approach for Brain Tumor Detection and Classification Using Fuzzy Thresholding and Deep Learning Algorithms by Nashaat M. Hussain Hassan, Wadii Boulila

“…The proposed method is evaluated across three large public datasets comprising more than 23,000 MRI images. …”
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Decision Tree-Based Maneuver Prediction for Driver Rear-End Risk-Avoidance Behaviors in Cut-In Scenarios by Manjiang Hu, Yuan Liao, Wenjun Wang, Guofa Li, Bo Cheng, Fang Chen

“…The prediction accuracy of the extracted classification rules was 79.2% for the training data set and 80.3% for the test data set. …”
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Ensemble-based sesame disease detection and classification using deep convolutional neural networks (CNN) by Abenet Alazar Hailu, Banchalem Chebudie Kassa, Esubalew Asmare Desta, Fikadu Berie Adugna, Ayodeji Olalekan Salau

“…The proposed ensemble model integrates these individual networks to enhance classification accuracy and improve generalization across diverse datasets. …”
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Optimizing food pantry stocking through client preferences: a novel elicitation and classification process by Benjamin F. Morrow, Lauren Berrings Davis, Steven Jiang, Nikki McCormick

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Explainable CNN for brain tumor detection and classification through XAI based key features identification by Shagufta Iftikhar, Nadeem Anjum, Abdul Basit Siddiqui, Masood Ur Rehman, Naeem Ramzan

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A Machine Learning Approach to Identifying Risk Factors for Long COVID-19 by Rhea Machado, Reshen Soorinarain Dodhy, Atharve Sehgal, Kate Rattigan, Aparna Lalwani, David Waynforth

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Advances in Corneal Diagnostics Using Machine Learning by Noor T. Al-Sharify, Salman Yussof, Nebras H. Ghaeb, Zainab T. Al-Sharify, Husam Yahya Naser, Sura M. Ahmed, Ong Hang See, Leong Yeng Weng

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Hybrid Recurrent Neural Network and Decision Tree Scheduling for Energy-Efficient Resource Allocation in Cloud Computing by Sefati Seyed Salar, Vulpe Alexandru, Popovici Eduard, Fratu Octavian

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