Ravita Chahar, Ashutosh Kumar Dubey^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-65, 2026, DOI:10.32604/cmc.2025.066990 - 10 November 2025

Abstract Objective: The increasing global prevalence of mental health disorders highlights the urgent need for the development of innovative diagnostic methods. Conditions such as anxiety, depression, stress, bipolar disorder (BD), and autism spectrum disorder (ASD) frequently arise from the complex interplay of demographic, biological, and socioeconomic factors, resulting in aggravated symptoms. This review investigates machine intelligence approaches for the early detection and prediction of mental health conditions. Methods: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework was employed to conduct a systematic review and analysis covering the period 2018 to 2025. The potential… More >

Somayah Albaradei^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 2937-2970, 2025, DOI:10.32604/cmes.2025.072584 - 23 December 2025

Abstract Cancer deaths and new cases worldwide are projected to rise by 47% by 2040, with transitioning countries experiencing an even higher increase of up to 95%. Tumor severity is profoundly influenced by the timing, accuracy, and stage of diagnosis, which directly impacts clinical decision-making. Various biological entities, including genes, proteins, mRNAs, miRNAs, and metabolites, contribute to cancer development. The emergence of multi-omics technologies has transformed cancer research by revealing molecular alterations across multiple biological layers. This integrative approach supports the notion that cancer is fundamentally driven by such alterations, enabling the discovery of molecular signatures… More > Graphic Abstract

Deema Alzamil^1,2,*, Bader Alkhamees², Mohammad Mehedi Hassan^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 2971-3027, 2025, DOI:10.32604/cmes.2025.070867 - 23 December 2025

Abstract Breast cancer diagnosis relies heavily on many kinds of information from diverse sources—like mammogram images, ultrasound scans, patient records, and genetic tests—but most AI tools look at only one of these at a time, which limits their ability to produce accurate and comprehensive decisions. In recent years, multimodal learning has emerged, enabling the integration of heterogeneous data to improve performance and diagnostic accuracy. However, doctors cannot always see how or why these AI tools make their choices, which is a significant bottleneck in their reliability, along with adoption in clinical settings. Hence, people are adding… More >

Theano Makridou¹, Elena Vlastou², Vasilios Kouloulias³, Efstathios P. Efstathopoulos⁴, Kalliopi Platoni^4,*

Oncology Research, Vol.33, No.12, pp. 3611-3632, 2025, DOI:10.32604/or.2025.069101 - 27 November 2025

Abstract Nanomedicine has evolved significantly over the last decades and expanded its applications in pediatric oncology, which represents a special domain with unique patients and distinct requirements. Τhe need for early cancer diagnosis and more effective and targeted therapies aiming to increase the pediatric patients’ survival rates and minimize the treatment-related side effects to survivors is profound. Nanoparticles (NPs) come as a beacon of hope to provide sensitive cancer diagnostic tools and assist contrast agents’ transport to the malignant tumors. Besides, NPs could be designed to deliver targeted drugs and genes to tumors, minimizing the medicine-related… More >

Hiroshi Yoshida^1,*, Mayumi Kobayashi Kato²

Oncology Research, Vol.33, No.12, pp. 3701-3730, 2025, DOI:10.32604/or.2025.068432 - 27 November 2025

Abstract Ovarian endometrioid carcinoma (OEC) accounts for ~10% of epithelial ovarian cancers and displays broad morphologic diversity that complicates diagnosis and grading. Recent data show that the endometrial cancer molecular taxonomy (DNA polymerase epsilon, catalytic subunit [POLE]-ultramutated, mismatch repair-deficient [MMRd], p53-abnormal, no specific molecular profile [NSMP]) also applies to OEC, and that OEC is enriched for Lynch syndrome–associated tumors, supporting routine MMR testing. We aimed to synthesize contemporary evidence spanning epidemiology, histopathology and immunophenotype, diagnostic pitfalls and differential diagnosis, and to evaluate the clinical utility of The Cancer Genome Atlas (TCGA)-surrogate molecular classification for risk stratification; More >

Huihui Yang¹, Saif Ur Rehman Khan^2,*, Omair Bilal², Chao Chen^1,*, Ming Zhao²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2401-2434, 2025, DOI:10.32604/cmes.2025.072148 - 26 November 2025

Abstract Detecting Alzheimer’s disease is essential for patient care, as an accurate diagnosis influences treatment options. Classifying dementia from non-dementia in brain MRIs is challenging due to features such as hippocampal atrophy, while manual diagnosis is susceptible to error. Optimal computer-aided diagnosis (CAD) systems are essential for improving accuracy and reducing misclassification risks. This study proposes an optimized ensemble method (CEOE-Net) that initiates with the selection of pre-trained models, including DenseNet121, ResNet50V2, and ResNet152V2 for unique feature extraction. Each selected model is enhanced with the inclusion of a channel attention (CA) block to improve the feature… More >

Qiang Ma^1,2,3,4, Zepeng Li^1,2, Kai Yang^1,2,*, Shaofeng Zhang^1,2, Zhuopei Wei^1,2

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1607-1634, 2025, DOI:10.32604/sdhm.2025.069876 - 17 November 2025

Abstract Effective fault identification is crucial for bearings, which are critical components of mechanical systems and play a pivotal role in ensuring overall safety and operational efficiency. Bearings operate under variable service conditions, and their diagnostic environments are complex and dynamic. In the process of bearing diagnosis, fault datasets are relatively scarce compared with datasets representing normal operating conditions. These challenges frequently cause the practicality of fault detection to decline, the extraction of fault features to be incomplete, and the diagnostic accuracy of many existing models to decrease. In this work, a transfer-learning framework, designated DSCNN-HA-TL,… More >

Mingxing Wu¹, Chengzhen Li¹, Xinyan Feng¹, Fei Chen², Yingchun Feng¹, Huihui Song¹, Wenyu Wang³, Faye Zhang^3,*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1473-1487, 2025, DOI:10.32604/sdhm.2025.069811 - 17 November 2025

Abstract As a core component of power systems, the operational status of transformers directly affects grid stability. To address the problem of “domain shift” in cross-domain fault diagnosis, this paper proposes a memory-enhanced dual-stream network (MemFuse-DSN). The method reconstructs the feature space by selecting and enhancing multi-source domain samples based on similarity metrics. An adaptive weighted dual-stream architecture is designed, integrating gradient reversal and orthogonality constraints to achieve efficient feature alignment. In addition, a novel dual dynamic memory module is introduced: the task memory bank is used to store high-confidence class prototype information, and adopts an More >

Raidizon Mercedes, Eric Eidelman, Michael Mawhorter, Max Yudovich, Alireza Aminsharifi^*

Canadian Journal of Urology, Vol.32, No.5, pp. 515-520, 2025, DOI:10.32604/cju.2025.067973 - 30 October 2025

Abstract Background: Spontaneous rupture of the urinary bladder (SRUB) is a rare condition characterized by bladder rupture without any trauma or previous instrumentation. Diagnosing SRUB can be challenging, leading to potential delays in treatment and significant morbidity. Case description: We present a case of a 75-year-old male with a complex medical history, including atrial fibrillation, systemic lupus erythematosus, antiphospholipid syndrome, and chronic anticoagulation, who developed sudden onset gross hematuria and abdominal pain following bilateral internal iliac artery angioembolization for a spontaneous pelvic hematoma in the setting of supratherapeutic anticoagulation. Extraperitoneal bladder perforation was confirmed by CT cystogram.… More >

Sadia Fatima¹, Fadl Dahan^2,*, Jamal Hussain Shah¹, Refan Almohamedh², Mohammed Aloqaily², Samia Riaz¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 971-994, 2025, DOI:10.32604/cmes.2025.070272 - 30 October 2025

Abstract The human gastrointestinal (GI) tract is influenced by numerous disorders. If not detected in the early stages, they may result in severe consequences such as organ failure or the development of cancer, and in extreme cases, become life-threatening. Endoscopy is a specialised imaging technique used to examine the GI tract. However, physicians might neglect certain irregular morphologies during the examination due to continuous monitoring of the video recording. Recent advancements in artificial intelligence have led to the development of high-performance AI-based systems, which are optimal for computer-assisted diagnosis. Due to numerous limitations in endoscopic image… More >