Tawfeeq Shawly¹, Ahmed A. Alsheikhy^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4161-4179, 2025, DOI:10.32604/cmc.2025.061497 - 06 March 2025

Abstract A healthy brain is vital to every person since the brain controls every movement and emotion. Sometimes, some brain cells grow unexpectedly to be uncontrollable and cancerous. These cancerous cells are called brain tumors. For diagnosed patients, their lives depend mainly on the early diagnosis of these tumors to provide suitable treatment plans. Nowadays, Physicians and radiologists rely on Magnetic Resonance Imaging (MRI) pictures for their clinical evaluations of brain tumors. These evaluations are time-consuming, expensive, and require expertise with high skills to provide an accurate diagnosis. Scholars and industrials have recently partnered to implement… More >

Amel Ksibi^1,*, Mohammed Zakariah², Latifah Almuqren¹, Ala Saleh Alluhaidan¹

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4093-4116, 2025, DOI:10.32604/cmc.2025.059615 - 06 March 2025

Abstract The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches, such as signature-based detection, are no longer effective due to the continuously advancing level of sophistication. To resolve this problem, efficient and flexible malware detection tools are needed. This work examines the possibility of employing deep CNNs to detect Android malware by transforming network traffic into image data representations. Moreover, the dataset used in this study is the CIC-AndMal2017, which contains 20,000 instances of network traffic across five distinct malware categories: a.… More >

Mohammed Salih Ahmed¹, Atta Rahman^2,*, Yahya Alhabboub¹, Khalid Alzahrani¹, Hassan Baragbah¹, Basel Altaha¹, Hussein Alkatout¹, Sardar Asad Ali Biabani^3,4, Rashad Ahmed⁵, Aghiad Bakry²

Intelligent Automation & Soft Computing, Vol.40, pp. 149-175, 2025, DOI:10.32604/iasc.2025.059080 - 12 February 2025

Abstract This study rigorously evaluates the potential of transfer learning in diagnosing retinal eye diseases using advanced models such as YOLOv8, Xception, ConvNeXtTiny, and VGG16. All models were trained on the esteemed RFMiD dataset, which includes images classified into six critical categories: Diabetic Retinopathy (DR), Macular Hole (MH), Diabetic Neuropathy (DN), Optic Disc Changes (ODC), Tesselated Fundus (TSLN), and normal cases. The research emphasizes enhancing model performance by prioritizing recall metrics, a crucial strategy aimed at minimizing false negatives in medical diagnostics. To address the challenge of imbalanced data, we implemented effective preprocessing techniques, including cropping,… More >

WEITAO ZHENG¹, DONG JIANG², SONGEN CHEN¹, MEILING WU¹, BAOQI YAN², JIAHUI ZHAI², YUNQIANG SHI², BIN XIE¹, XINGWANG XIE², KANGHONG HU^1,*, WENXUE MA^3,*

Oncology Research, Vol.32, No.12, pp. 1837-1850, 2024, DOI:10.32604/or.2024.056565 - 13 November 2024

Abstract Objectives: The Kirsten rat sarcoma virus (KRAS) G12D oncogenic mutation poses a significant challenge in treating solid tumors due to the lack of specific and effective therapeutic interventions. This study aims to explore innovative approaches in T cell receptor (TCR) engineering and characterization to target the KRAS G12D_7-16 mutation, providing potential strategies for overcoming this therapeutic challenge. Methods: In this innovative study, we engineered and characterized two T cell receptors (TCRs), KDA11-01 and KDA11-02 with high affinity for the KRAS G12D_7-16 mutation. These TCRs were isolated from tumor-infiltrating lymphocytes (TILs) derived from tumor tissues of patients More >

Saad Akbar^1,2, Humera Azam¹, Sulaiman Sulmi Almutairi^3,*, Omar Alqahtani⁴, Habib Shah⁴, Aliya Aleryani⁴

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1075-1104, 2024, DOI:10.32604/cmc.2024.050913 - 18 July 2024

Abstract The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic tools. In this article, a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19, pneumonia, and normal conditions in chest X-ray images (CXIs) is proposed coupled with Explainable Artificial Intelligence (XAI). Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3, VGG16, and VGG19 that excel in the task of feature extraction. The methodology is further enhanced by the inclusion of the t-SNE (t-Distributed… More >

Awais Khan¹, Chomyong Kim², Jung-Yeon Kim², Ahsan Aziz¹, Yunyoung Nam^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1729-1755, 2024, DOI:10.32604/cmes.2024.049618 - 20 May 2024

Abstract Sleep posture surveillance is crucial for patient comfort, yet current systems face difficulties in providing comprehensive studies due to the obstruction caused by blankets. Precise posture assessment remains challenging because of the complex nature of the human body and variations in sleep patterns. Consequently, this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification, thereby enhancing the analysis of body position and comfort. This method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras, which depict six commonly adopted postures: supine,… More > Graphic Abstract

Imad Saud Al Naimi^1,2,*, Syed Alwee Aljunid Syed Junid¹, Muhammad lmran Ahmad^1,*, K. Suresh Manic^2,3

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2585-2608, 2024, DOI:10.32604/cmc.2024.046461 - 15 May 2024

Abstract Augmentation of abnormal cells in the brain causes brain tumor (BT), and early screening and treatment will reduce its harshness in patients. BT’s clinical level screening is usually performed with Magnetic Resonance Imaging (MRI) due to its multi-modality nature. The overall aims of the study is to introduce, test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans, facilitating improved accuracy. The research intends to devise a reliable framework for detecting the BT region in the two-dimensional (2D) MRI slice, and identifying its class with improved… More >

JIYU WANG^1,#, LIUYING YI^2,#, KEKE HUANG¹, YANGYANG WANG¹, HUIPING WANG¹, ZHIMIN ZHAI^1,*

BIOCELL, Vol.48, No.3, pp. 453-462, 2024, DOI:10.32604/biocell.2024.047871 - 15 March 2024

Abstract Background: The primary cause of treatment failure in patients with refractory or relapsed B-cell non-Hodgkin lymphoma (r/r B-NHL) is resistance to current therapies, and therapy-induced senescence (TIS) stands out as a crucial mechanism contributing to tumor drug resistance. Here, we analyzed SENEX/Rho GTPase Activating Protein 18 (ARHGAP18) expression and prognostic significance in doxorubicin-induced B-NHL-TIS model and r/r B-NHL patients, investigating its target in B-NHL cell senescence and the effect of combining specific inhibitors on apoptosis resistance in B-NHL-TIS cells. Methods: Raji cells were transfected with the human SENEX shRNA recombinant lentiviral vector (Sh-SENEX) and the empty vector… More >

Heba M. El-Hoseny^1,*, Heba F. Elsepae², Wael A. Mohamed², Ayman S. Selmy²

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1855-1872, 2023, DOI:10.32604/cmc.2023.042107 - 29 November 2023

Abstract Diabetic retinopathy is a critical eye condition that, if not treated, can lead to vision loss. Traditional methods of diagnosing and treating the disease are time-consuming and expensive. However, machine learning and deep transfer learning (DTL) techniques have shown promise in medical applications, including detecting, classifying, and segmenting diabetic retinopathy. These advanced techniques offer higher accuracy and performance. Computer-Aided Diagnosis (CAD) is crucial in speeding up classification and providing accurate disease diagnoses. Overall, these technological advancements hold great potential for improving the management of diabetic retinopathy. The study’s objective was to differentiate between different classes… More >

Lei Wang¹, Runying Wang¹, Yi Li³, Yichen Zhao^1,*, Degang Zhao^1,2,*

Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 3063-3075, 2023, DOI:10.32604/phyton.2023.043803 - 24 October 2023

Abstract Adventitious root formation poses a major constraint on the tissue culture and genetic transformation of Eucommia ulmoides. Micrografting offers a new method for the transplantation of genetic transformation, and its success depends on the formation of graft unions. This study used transgenic rootless test-tube seedlings as scions and seedlings from seed as rootstocks during micrografting to avoid the rooting issues that occur during tissue culture and to investigate the role of the EuEG1 gene in the graft healing process. We found that the EuEG1 gene is a vital regulator of graft, and its overexpression contributes to the… More >