ADVANCEMENTS IN ALZHEIMER’S DIAGNOSIS THROUGH MRI USING BAYESIAN CONVOLUTIONAL NEURAL NETWORKS AND VARIATIONAL INFERENCE by Alifia Ardha Nareswari, Dina Tri Utari

“…We use a dataset scenario of 80% for training and 20% for testing, 100x100 pixels, kernel size 3x3, and optimizer Adam with epoch 200. The accuracy of the image classification process is 80%. …”
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Support Vector Machine Berbasis Feature Selection Untuk Sentiment Analysis Kepuasan Pelanggan Terhadap Pelayanan Warung dan Restoran Kuliner Kota Tegal by Oman Somantri, Dyah Apriliani

“…Hasil penelitian menunjukan bahwa tingkat akurasi terbaik dihasilkan oleh model SVM-IG dengan tingkat akurasi terbaik sebesar 72,45% mengalami peningkatan sekitar 3,08% yang awalnya 69.36%. …”
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Elevating Accuracy: Enhanced Feature Selection Methods for Type 2 Diabetes Prediction by Ghazaleh Kakavand Teimoory, MohammadReza Keyvanpour

“…Previous research has utilized various algorithms like Naïve Bayes, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and decision trees for patient classification. In this study using the Pima dataset, we applied a preprocessing technique that utilized the most important features identified by the Random Forest algorithm and we used an ensemble method combining the SVM algorithm and Naïve Bayes for the model. …”
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Characterization of Hazelnut Trees in Open Field Through High-Resolution UAV-Based Imagery and Vegetation Indices by Maurizio Morisio, Emanuela Noris, Chiara Pagliarani, Stefano Pavone, Amedeo Moine, José Doumet, Luca Ardito

“…For each quadrant, nine different vegetation indices (VIs) were computed, and in parallel, each tree quadrant was tagged as “healthy/unhealthy” by visual inspection. Three supervised binary classification algorithms were used to build models capable of predicting the status of the tree quadrant, using the VIs as predictors. …”
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Discovering sequential patterns and interrelations among multiple diseases in electronic medical records using cSPADE algorithm by He Ma, Qianxin Huang, Hong Zhang, Hui Song, Bo Zhang, Ying Liu, Lin Zhang

“…Methods Patient identity information, visit dates, and diagnostic data were aggregated from the electronic medical record databases of three large general hospitals. The diagnostic information included the International Classification of Diseases, Tenth Revision (ICD-10) codes, along with their corresponding descriptions. …”
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Anomaly Detection in Industrial Machine Sounds Using High-Frequency Features and Gate Recurrent Unit Networks by Thi-Thu-Huong Le, Andro Aprila Adiputra, Jiwon Yun, Howon Kim

“…This paper proposes a comprehensive approach that leverages machine learning (ML) and deep learning (DL) techniques to address these challenges. Using three datasets, the Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization 2022 (MIMII DG 2022), the Detection and Classification of Acoustic Scenes and Events (DCASE) 2022, and DCASE 2024, we evaluate the performance of various ML and DL models under different experimental conditions. …”
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Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

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Assessing the Correlation Between GMP Deviations and Potential Quality Defects of Medicinal Products: the Result of the Survey of Qualified Persons by V. A. Orlov, V. N. Shestakov

“…In the framework of the study, authors used the model of gradation of quality defects of the medicinal products into 3 classes (class I, II and III) according to the rate of their significance as indicated in the PIC/S and EMA guidelines. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Costs were reported in 2020/21 prices and discounted at 3.5% per annum. The model estimated the mean costs incurred and benefits accrued associated with each strategy for people entering the model at 60 years old. …”
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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

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Fault Diagnosis of Semi-Supervised Electromechanical Transmission Systems Under Imbalanced Unlabeled Sample Class Information Screening by Chaoge Wang, Pengpeng Jia, Xinyu Tian, Xiaojing Tang, Xiong Hu, Hongkun Li

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ROPGCViT: A Novel Explainable Vision Transformer for Retinopathy of Prematurity Diagnosis by Mustafa Yurdakul, Kubra Uyar, Sakir Tasdemir, Irfan Atabas

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Voice biomarkers as prognostic indicators for Parkinson’s disease using machine learning techniques by Ifrah Naeem, Allah Ditta, Tehseen Mazhar, Muhammad Anwar, Mamoon M. Saeed, Habib Hamam

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Racial Disparities in Comorbidity Patterns of Early-Onset Liver Cancer: A Machine Learning Analysis by Bingya Ma MSc, Kai Zheng PhD, Fa-Chyi Lee MD, Yunxia Lu MD, PhD

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Using FastText-BERT to Extract Semantic Relations and Improve Sentiment Analysis of Persian Healthcare Service Reviews by Faezeh Forootan, Raouf Khayami, Pirooz Shamsinejad

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ChestXFusionNet: A Multimodal Deep Learning Framework for Predicting Chest Diseases from X-ray Images and Clinical Data by Shimbre Nivedita, Solanki Ram Kumar

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Eye-Guided Multimodal Fusion: Toward an Adaptive Learning Framework Using Explainable Artificial Intelligence by Sahar Moradizeyveh, Ambreen Hanif, Sidong Liu, Yuankai Qi, Amin Beheshti, Antonio Di Ieva

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Explainable AI for early malaria detection using stacked-LSTM and attention mechanisms by Adil Gaouar, Souaad Hamza Cherif, Abdellatif Rahmoun, Mostafa El Habib Daho

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Deep learning assisted non-invasive lymph node burden evaluation and CDK4/6i administration in luminal breast cancer by Yuhan Liu, Jinlin Ye, Zecheng He, Mingyue Wang, Changjun Wang, Jie Lang, Yidong Zhou, Wei Zhang

“…In a multicenter cohort of 411 patients, LNPN demonstrated robust performance, achieving an AUC of 0.92 for binary lymph node burden classification (N0 vs. N+) and 0.82 for ternary lymph node burden classification (N0/N1–3/N ≥ 4). …”
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A Deep Learning Approach Based on Interpretable Feature Importance for Predicting Sports Results by Bendiaf Messaoud, Khelifi Hakima, Mohdeb Djamila, Belazzoug Mouhoub, Saifi Abdelhamid

“…As a multiclass classification problem with three classes, each match can have three possible outcomes. …”
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