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We tackle the challenging problem of single-source domain generalization (DG) for medical image segmentation, where we train a network on one domain (e.g., CT) and directly apply it to a different domain (e.g., MR) witho...

In the face of socioeconomic challenges, this paper develops and empirically demonstrates the Gondauri Index (GI) as a reproducible, diagnostics-first composite framework for benchmarking macro-financial resilience acros...

The effect of imbalanced data on the optical character recognition of Braille text is investigated by applying two techniques to a set of convolutional neural network image classification models. A multilabel classificat...

Abstract Background Thalassemia is the most prevalent single-gene disorder in Sri Lanka, imposing a significant socioeconomic and healthcare burden. Early carrier detection is essential for genetic counselling and the pr...

Abstract A compartmental mathematical model was developed to examine the transmission dynamics of chikungunya, integrating media awareness and optimal control strategies. Both asymptomatic and symptomatic infectious cate...

Kaissar Tabynov,1,2,* Kairat Tabynov,2,3 Nikolai Petrovsky4,* 1International Center for Vaccinology, Kazakh National Agrarian Research University, Almaty, Kazakhstan; 2Preclinical Research Laboratory with...

Diabetic retinopathy (DR) is one of the leading causes of preventable blindness worldwide, making timely and accurate detection crucial for effective management. This study introduces DR-NetFusion, a novel hybrid deep le...

The paper deals with modeling three-dimensional illumination distribution from light sourсes using artificial neural network (ANN). This problem is especially relevant in greenhouse irradiation systems due to the design...

The article presents the developed algorithm and software for automated monitoring of strawberry plant growth using neural network technologies. The YOLO11x and YOLOx-seg models, pre-trained by transfer learning, are ada...

Abstract Introduction This study aimed to develop a deep learning-based system to automatically assess patient positioning compliance in chest radiographs, focusing on cervical spine visibility, scapular overlap, and cos...

The application of Artificial Intelligence (AI) in project management is transforming decision-making processes, enhancing task execution, and improving risk management. This study aimed to elucidate the challenges raise...

Abstract Background Maxillary sinus (MS) floor elevation using the lateral window approach is a predictable technique for bone augmentation in the posterior maxilla. However, injury to the posterior superior alveolar art...

The performances of the navigation systems used for different flight phases especially in the landing of an aircraft must be very high. The International Civil Aviation Organization defines the standards which must meet ...

Abstract Background Intramuscular fat (IMF) accumulation in lumbar‑spine muscles is associated with sarcopenia, low‑back pain and poorer surgical outcomes. Dixon MRI allows the measurement of IMF with voxel-wise fat ...

O aperfeiçoamento nos últimos anos das lentes de aumento e dos microscópios, bem como o desenvolvimento de técnicas de preparação de amostras, disponibilizou excelentes ferramentas para pesquisas nas diversas área...

Abstract Reliable interpretation of clinical imaging requires integrating complementary evidence across modalities, yet most AI systems remain limited by single-modality analysis and poor generalization across institutio...

Abstract Accurate early detection of clinically significant prostate cancer is crucial for improving patient outcomes. However, traditional diagnostic methods such as Digital Rectal Exam and Prostate-Specific Antigen (PS...

Abstract Objectives Gastroesophageal reflux disease (GERD) is estimated to affect up to one-quarter of the Italian population, generating immense treatment costs. An emergent surgical treatment involving implantation of ...

Abstract We introduce a decoding framework for correlated errors in quantum LDPC codes under circuit-level noise. Our approach is a graph augmentation and rewiring for inference (GARI) method, which modifies the correlat...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

Abstract Background Collagenous colitis (CC) is diagnosed histologically and is characterised by a thickened subepithelial collagen band together with inflammatory and epithelial changes. Although routine haematoxylin an...

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

IntroductionLiver diseases continue to impose a major global health burden, and therapeutic progress is constrained by the limited availability of validated small-molecule modulators. TEAD4, a central Hippo-YAP effector,...

India’s strategic community has long been preoccupied with conventional military threats, but the security implications of environmental change remain underexplored. This paper examines the depletion of natural springs...