A review on optimization of Wilms tumour management using radiomics DOI Creative Commons
Maryam Alhashim, Noushin Anan, Mahbubunnabi Tamal

et al.

BJR|Open, Journal Year: 2023, Volume and Issue: 6(1)

Published: Dec. 12, 2023

Wilms tumour, a common paediatric cancer, is difficult to treat in low- and middle-income countries due limited access imaging. Artificial intelligence (AI) has been introduced for staging, detecting, classifying tumours, aiding physicians decision-making. However, challenges include algorithm accuracy, translation into conventional diagnosis, reproducibility, reliability. As AI technology advances, radiomics, an tool, emerges extract tumour morphology stage information.

Language: Английский

Comprehensive machine and deep learning analysis of sensor-based human activity recognition DOI
Hossam Magdy Balaha, Asmaa El-Sayed Hassan

Neural Computing and Applications, Journal Year: 2023, Volume and Issue: 35(17), P. 12793 - 12831

Published: March 8, 2023

Language: Английский

Citations

32

A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images DOI Creative Commons

Aya A. Abd El-Khalek,

Hossam Magdy Balaha,

Norah Saleh Alghamdi

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 29, 2024

Abstract The increase in eye disorders among older individuals has raised concerns, necessitating early detection through regular examinations. Age-related macular degeneration (AMD), a prevalent condition over 45, is leading cause of vision impairment the elderly. This paper presents comprehensive computer-aided diagnosis (CAD) framework to categorize fundus images into geographic atrophy (GA), intermediate AMD, normal, and wet AMD categories. crucial for precise age-related enabling timely intervention personalized treatment strategies. We have developed novel system that extracts both local global appearance markers from images. These are obtained entire retina iso-regions aligned with optical disc. Applying weighted majority voting on best classifiers improves performance, resulting an accuracy 96.85%, sensitivity 93.72%, specificity 97.89%, precision 93.86%, F1 ROC 95.85%, balanced 95.81%, sum 95.38%. not only achieves high but also provides detailed assessment severity each retinal region. approach ensures final aligns physician’s understanding aiding them ongoing follow-up patients.

Language: Английский

Citations

14

A Multidisciplinary Hyper-Modeling Scheme in Personalized In Silico Oncology: Coupling Cell Kinetics with Metabolism, Signaling Networks, and Biomechanics as Plug-In Component Models of a Cancer Digital Twin DOI Open Access
Eleni Kolokotroni, Daniel Abler,

Alokendra Ghosh

et al.

Journal of Personalized Medicine, Journal Year: 2024, Volume and Issue: 14(5), P. 475 - 475

Published: April 29, 2024

The massive amount of human biological, imaging, and clinical data produced by multiple diverse sources necessitates integrative modeling approaches able to summarize all this information into answers specific questions. In paper, we present a hypermodeling scheme combine models cancer aspects regardless their underlying method or scale. Describing tissue-scale cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant metabolism, cell-signaling pathways that regulate the cellular response therapy, hypermodel integrates mutation, miRNA expression, data. constituting hypomodels, as well orchestration links, are described. Two types, Wilms (nephroblastoma) non-small lung cancer, addressed proof-of-concept study cases. Personalized simulations actual anatomy patient have been conducted. has also applied predict control after radiotherapy relationship between proliferative activity neoadjuvant chemotherapy. Our innovative holds promise digital twin-based decision support system core future in silico trial platforms, although additional retrospective adaptation validation necessary.

Language: Английский

Citations

9

Artificial Intelligence in Pediatric Urology DOI
Hsin‐Hsiao Scott Wang, Ranveer Vasdev, Caleb P. Nelson

et al.

Urologic Clinics of North America, Journal Year: 2023, Volume and Issue: 51(1), P. 91 - 103

Published: Sept. 15, 2023

Language: Английский

Citations

12

Predicting response of hepatoblastoma primary lesions to neoadjuvant chemotherapy through contrast-enhanced computed tomography radiomics DOI Creative Commons

Yanlin Yang,

Haoru Wang,

Jiajun Si

et al.

Journal of Cancer Research and Clinical Oncology, Journal Year: 2024, Volume and Issue: 150(5)

Published: April 30, 2024

To investigate the clinical value of contrast-enhanced computed tomography (CECT) radiomics for predicting response primary lesions to neoadjuvant chemotherapy in hepatoblastoma.

Language: Английский

Citations

4

Applications of Artificial Intelligence for Pediatric Cancer Imaging DOI
Shashi B. Singh, Amir Hossein Sarrami, Sergios Gatidis

et al.

American Journal of Roentgenology, Journal Year: 2024, Volume and Issue: 223(2)

Published: May 29, 2024

Artificial intelligence (AI) is transforming the medical imaging of adult patients. However, its utilization in pediatric oncology remains constrained, part due to inherent scarcity data associated with childhood cancers. Pediatric cancers are rare, and technologies evolving rapidly, leading insufficient a particular type effectively train these algorithms. The small market size patients compared could also contribute this challenge, as driver commercialization. This review provides an overview current state AI applications for cancer imaging, including image acquisition, processing, reconstruction, segmentation, diagnosis, staging, treatment response monitoring. Although developments promising, impediments diverse anatomies growing children nonstandardized protocols have led limited clinical translation thus far. Opportunities include leveraging reconstruction algorithms achieve accelerated low-dose automating generation metric-based staging monitoring scores. Transfer learning adult-based models cancers, multiinstitutional sharing, ethical privacy practices rare will be keys unlocking full potential improving outcomes young

Language: Английский

Citations

4

Precise Prostate Cancer Assessment Using IVIM-Based Parametric Estimation of Blood Diffusion from DW-MRI DOI Creative Commons
Hossam Magdy Balaha, Sarah M. Ayyad, Ahmed Alksas

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(6), P. 629 - 629

Published: June 19, 2024

Prostate cancer is a significant health concern with high mortality rates and substantial economic impact. Early detection plays crucial role in improving patient outcomes. This study introduces non-invasive computer-aided diagnosis (CAD) system that leverages intravoxel incoherent motion (IVIM) parameters for the of prostate (PCa). IVIM imaging enables differentiation water molecule diffusion within capillaries outside vessels, offering valuable insights into tumor characteristics. The proposed approach utilizes two-step segmentation through use three U-Net architectures extracting tumor-containing regions interest (ROIs) from segmented images. performance CAD thoroughly evaluated, considering optimal classifier comparing diagnostic value commonly used apparent coefficient (ADC). results demonstrate combination central zone (CZ) peripheral (PZ) features Random Forest Classifier (RFC) yields best performance. achieves an accuracy 84.08% balanced 82.60%. showcases sensitivity (93.24%) reasonable specificity (71.96%), along good precision (81.48%) F1 score (86.96%). These findings highlight effectiveness accurately segmenting diagnosing PCa. represents advancement methods early PCa, showcasing potential machine learning techniques. developed solution has to revolutionize PCa diagnosis, leading improved outcomes reduced healthcare costs.

Language: Английский

Citations

4

Insights into Personalized Care Strategies for Wilms Tumor: A Narrative Literature Review DOI Creative Commons

Salma Karam,

Ahmad Gebreil,

Ahmed Alksas

et al.

Biomedicines, Journal Year: 2024, Volume and Issue: 12(7), P. 1455 - 1455

Published: June 30, 2024

Wilms tumor (WT), or nephroblastoma, is the predominant renal malignancy in pediatric population. This narrative review explores evolution of personalized care strategies for WT, synthesizing critical developments molecular diagnostics and treatment approaches to enhance patient-specific outcomes. We surveyed recent literature from last five years, focusing on high-impact research across major databases such as PubMed, Scopus, Web Science. Diagnostic advancements, including liquid biopsies diffusion-weighted MRI, have improved early detection precision. The prognostic significance genetic markers, particularly WT1 mutations miRNA profiles, discussed. Novel predictive tools integrating clinical data anticipate disease trajectory therapy response are explored. Progressive strategies, immunotherapy targeted agents HIF-2α inhibitors GD2-targeted immunotherapy, highlighted their role protocols, especially refractory recurrent WT. underscores necessity management supported by insights, with survival rates localized exceeding 90%. However, knowledge gaps persist therapies high-risk patients reduce long-term treatment-related morbidity. In conclusion, this highlights need ongoing research, outcomes emerging multi-omic inform decision-making, paving way more individualized pathways.

Language: Английский

Citations

4

Early detection of monkeypox: Analysis and optimization of pretrained deep learning models using the Sparrow Search Algorithm DOI Creative Commons
Amna Bamaqa, Waleed M. Bahgat, Yousry AbdulAzeem

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 102985 - 102985

Published: Sept. 30, 2024

Language: Английский

Citations

3

Comprehensive multimodal approach for Parkinson’s disease classification using artificial intelligence: insights and model explainability DOI
Hossam Magdy Balaha, Asmaa El-Sayed Hassan,

Ranaa Ahmed

et al.

Soft Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 15, 2025

Language: Английский

Citations

0