Varied Presentations Of Patients With Systemic Lupus Erythematosus – What Makes Pakistani Lupus Patients Different by Muhammad Shahzad Manzoor, Shamaila Mumtaz, Faran Maqbool, Darakhshaan Samar, Muhammad Hammas Adil, Javaria Malik

“…Methods: This prospective, cross-sectional study was undertaken at the Clinic for Arthritis and Rheumatic Diseases, Rawalpindi Teaching Hospital, Rawalpindi, Pakistan between January 2020 and June 2023, involving adult patients with SLE (classified based on 1997 revised ACR criteria). Demographic data, clinical and laboratory features, auto-antibody profile, disease duration, treatment history and organ damage (calculated by SLICC/ACR-DI) were recorded for all patients. …”
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Advancing Fractal Dimension Techniques to Enhance Motor Imagery Tasks Using EEG for Brain–Computer Interface Applications by Amr F. Mohamed, Vacius Jusas

“…For this purpose, all four classes provided in the BCI Competition IV 2a dataset are utilized with nine different combinations of seven FD methods: Katz, Petrosian, Higuchi, box-counting, MFDFA, DFA, and correlation dimension. The resulting features are then used to train five machine learning models: linear, Gaussian, polynomial support vector machine, regression tree, and stochastic gradient descent. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…In this paper, we propose a multimodality image registration network based on multistage transformation enhancement features (MTEF) to maintain the continuity of the deformation field. …”
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Electrohysterogram Data Augmentation Using Generative Adversarial Network for Pregnancy Outcome Prediction by Muhammad Omar Cheema, Zia Mohy-Ud-Din, Azhar Imran, Fawad Salam Khan, Mahmood Basil A. Al-Rawi, Mohammed A. El-Meligy, Jahan Zeb Gul

“…By successfully reducing class imbalance, the enhanced dataset makes it possible for machine learning models to be trained with resilience. Real and synthetic features did not differ significantly, according to statistical validation using a t-test (p > 0.05). …”
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Backpropagation Neural Network Implementation in Volumetric Modulated Arch Therapy of Brain Cancer Dose Prediction by Nafisa Imtiyaziffati Rasoma Muliarso, Prawito Prajitno, Dewa Ngurah Yudhi Prasada, Aloysius Putranto, Muhammad Fadli, Dwi Seno Kuncoro Sihono

“…Recent advancements in artificial intelligence (AI) offers an objective approach to improve the efficiency of VMAT planning.Material and Methods: In this study, the backpropagation neural network with 5-fold cross-validation model was employed to train the extracted Radiomics and dosiomics features from organ contours DICOM RT structure and dose distribution DICOM RT dose using 178 VMAT technique brain cancer patients. …”
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XAIHO: explainable AI leveraging hybrid optimized framework for liver cirrhosis detection by Prashant Kumar Mishra, Brijesh Kumar Chaurasia, Man Mohan Shukla

“…Additionally, transparency and interpretability are significantly improves using SHAP values and attention-based visualizations, providing meaningful insights into critical features such as bilirubin, albumin, and age. …”
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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…Machine learning (ML) models trained on disease datasets are more effective in detection and classification than the conventional methods with hand-crafted features highly dependent on pathologists’ expertise. …”
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Do Chatbots Exhibit Personality Traits? A Comparison of ChatGPT and Gemini Through Self-Assessment by W. Wiktor Jedrzejczak, Joanna Kobosko

“…The underlying design of large language models (LLMs), trained on vast amounts of human texts, implies that chatbots based on them will almost inevitably retain some human personality traits. …”
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Accurate and Robust Stellar Rotation Periods Catalog for 82771 Kepler Stars Using Deep Learning by Ilay Kamai, Hagai B. Perets

“…The model utilizes a dual-branch architecture combining long short-term memory and transformer components to capture temporal and global data features. We train LightPred on self-supervised contrastive pretraining and simulated light curves generated using a realistic spot model. …”
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Social and psychological adaptation of foreign students in a Russian university by O. S. Belova, A. G. Soloviev, A. V. Parnyakov

“…The need to study foreign students’ social and psychological adaptation in medical universities is caused by the increased need to train high-qualified doctors not only in our country, but also in the world community.The goal was to identify the features of social and psychological adaptation of foreign first-year students of the medical University.Methods. …”
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Discovery of novel TACE inhibitors using graph convolutional network, molecular docking, molecular dynamics simulation, and Biological evaluation. by Muhammad Yasir, Jinyoung Park, Eun-Taek Han, Jin-Hee Han, Won Sun Park, Mubashir Hassan, Andrzej Kloczkowski, Wanjoo Chun

“…Using RDKit, a cheminformatics toolkit, we extracted molecular features from these compounds. We applied the GraphConvMol model within the DeepChem framework, which utilizes graph convolutional networks, to build a predictive model based on the DUD-E datasets. …”
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Generative Image Steganography via Encoding Pose Keypoints by Yi Cao, Wentao Ge, Chengsheng Yuan, Quan Wang

“…This method employs an LSTM-based sequence generation model to embed secret information into the generation process of pose keypoint sequences. …”
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NeuralACT: Accounting Analytics Using Neural Network for Real-Time Decision Making From Big Data by Leonidas Theodorakopoulos, Alexandra Theodoropoulou, Georgios Kampiotis, Ioanna Kalliampakou

“…It uses a Bidirectional Long Short-Term Memory (BiLSTM) network trained with Visegrad Group Companies (VGC) dataset customized and improved for accounting features prediction. …”
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SOuLMuSiC, a novel tool for predicting the impact of mutations on protein solubility by Simone Attanasio, Jean Kwasigroch, Marianne Rooman, Fabrizio Pucci

“…To assist scientists in designing proteins with improved solubility and better understand solubility-related diseases, we introduce SOuLMuSiC, a computational tool for the fast and accurate prediction of the impact of single-site mutations on protein solubility. Our model is based on a simple artificial neural network that takes as input a series of features, including biophysical properties of wild-type and mutated residues, energetic values computed using various statistical potentials, and mutational scores derived from protein language models. …”
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Determinação da cobertura do solo por análise de imagens e redes neurais Soil cover determination using image analysis and neural networks by Carlos A. A. Varella, Francisco de A. de C. Pinto, Daniel M. de Queiroz, Darly G. de Sena Júnior

“…<br>An image classification algorithm was developed to estimate the soil cover based on artificial neural networks (ANN) trained by back-propagation algorithm. …”
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Design a new scheme for image security using a deep learning technique of hierarchical parameters by Khazaal Yasmine M., Falih Mohanaed Ajmi, Majeed Abbas Hamid

“…Convolutional neural networks are used in automatic learning to extract hierarchical features from an image, and to ensure adaptability, the model is trained on a variety of images. …”
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Mathematical algorithm for the automatic recognition of intestinal parasites. by Alicia Alva, Carla Cangalaya, Miguel Quiliano, Casey Krebs, Robert H Gilman, Patricia Sheen, Mirko Zimic

“…Parasitic infections are generally diagnosed by professionals trained to recognize the morphological characteristics of the eggs in microscopic images of fecal smears. …”
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A Data-Driven Intelligent Methodology for Developing Explainable Diagnostic Model for Febrile Diseases by Constance Amannah, Kingsley Friday Attai, Faith-Michael Uzoka

“…The system features an intuitive interface, patient record management, and AI-driven diagnostic insights with visual and textual explanations. …”
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Integrating AutoGluon for Real-Time Monitoring and Classification of Dental Equipment Performance by Muxiu Yang, Fengzhou Li, Wenfeng Qiu

“…Temperature and vibration were the most influential features in predicting equipment states based on the SHAP analysis. …”
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Real-Time Acoustic Detection of Critical Incidents in Smart Cities Using Artificial Intelligence and Edge Networks by Ioannis Saradopoulos, Ilyas Potamitis, Stavros Ntalampiras, Iraklis Rigakis, Charalampos Manifavas, Antonios Konstantaras

“…These devices host an audio transformer model trained on the AudioSet dataset, enabling the real-time classification and timestamping of audio events with high accuracy. …”
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