Challenges for Ethics Review Committees in Regulating Medical Artificial Intelligence Research

Indian Journal of Surgical Oncology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Language: Английский

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Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects

Frontiers in Pediatrics, Journal Year: 2025, Volume and Issue: 13

Published: April 17, 2025

Artificial Intelligence is revolutionizing prenatal diagnostics by enhancing the accuracy and efficiency of procedures. This review explores AI machine learning (ML) in early detection, prediction, assessment neural tube defects (NTDs) through ultrasound imaging. Recent studies highlight effectiveness techniques, such as convolutional networks (CNNs) support vector machines (SVMs), achieving detection rates up to 95% across various datasets, including fetal images, genetic data, maternal health records. SVM models have demonstrated 71.50% on training datasets 68.57% testing for NTD classification, while advanced deep (DL) methods report patient-level prediction 94.5% an area under receiver operating characteristic curve (AUROC) 99.3%. integration with genomic analysis has identified key biomarkers associated NTDs, Growth Associated Protein 43 (GAP43) Glial Fibrillary Acidic (GFAP), logistic regression 86.67% accuracy. Current AI-assisted technologies improved diagnostic accuracy, yielding sensitivity specificity 88.9% 98.0%, respectively, compared traditional 81.5% 92.2% specificity. systems also streamlined workflows, reducing median scan times from 19.7 min 11.4 min, allowing sonographers prioritize critical patient care. Advancements DL algorithms, Oct-U-Net PAICS, achieved recall precision 0.93 0.96, identifying abnormalities. Moreover, AI's evolving role research supports personalized prevention strategies enhances public awareness AI-generated messages. In conclusion, significantly improves leading greater As continues advance, it potential further enhance healthcare raise about ultimately contributing better outcomes.

Language: Английский

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The association between VEGF genetic variations and the risk of bronchopulmonary dysplasia in premature infants: a meta-analysis and systematic review

Frontiers in Pediatrics, Journal Year: 2024, Volume and Issue: 12

Published: Nov. 14, 2024

Objective Previous studies on the link between VEGF gene polymorphisms and bronchopulmonary dysplasia (BPD) have yielded inconsistent results. This meta-analysis sought to clarify relationship genetic variations in risk of BPD. Methods Data were collected from multiple databases, including PubMed, Scopus, EMBASE, CNKI, up January 5, 2024. Results Nineteen case-control analyzed, featuring 1,051 BPD cases 1,726 healthy neonates. The analysis included four −460T/C polymorphism (312 cases, 536 controls), −2578C/A (155 279 six +405G/C (329 385 five +936C/T (225 526 controls). suggests that may protect against (C vs. T: OR = 0 .715, 95% CI 0.543–0.941, p 0.017; CC TT: .478, 0.233–0.983, 0.045; CT + .435, 0.248–0.764, 0.004). No significant associations found −2578C/A, +405G/C, susceptibility. Conclusions indicates C allele offer protection observed for polymorphisms.

Language: Английский

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Machine Learning Applications in Placenta Accreta Spectrum Disorders

European Journal of Obstetrics & Gynecology and Reproductive Biology X, Journal Year: 2024, Volume and Issue: 25, P. 100362 - 100362

Published: Dec. 25, 2024

This review examines the emerging applications of machine learning (ML) and radiomics in diagnosis prediction placenta accreta spectrum (PAS) disorders, addressing a significant challenge obstetric care. It highlights recent advancements ML algorithms radiomic techniques that utilize medical imaging modalities like magnetic resonance (MRI) ultrasound for effective classification risk stratification PAS. The discusses efficacy various deep models, such as nnU-Net DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores. Furthermore, it underscores importance integrating quantitative features with clinical data to enhance accuracy optimize surgical planning. potential predict morbidity by analyzing demographic factors is also explored. Emphasizing need standardized methodologies ensure consistent feature extraction model performance, this advocates integration into workflows, aiming improve patient outcomes foster multidisciplinary approach high-risk pregnancies. Future research should focus on larger datasets validation biomarkers refine predictive models

Language: Английский

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The Role of Long Noncoding RNAs (LncRNAs) in the Pathogenesis of Chemoresistance in Endometrial Cancer: A Molecular Approach and Future Perspective

Indian Journal of Gynecologic Oncology, Journal Year: 2024, Volume and Issue: 23(1)

Published: Dec. 20, 2024

Language: Английский

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Loc646329 sponges miR-21 to reduce RAS/MAP kinase signaling pathway in oral squamous cell carcinoma (OSCC)

Naunyn-Schmiedeberg s Archives of Pharmacology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 14, 2024

Language: Английский

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Decoding the Genetic Landscape of Postoperative Nausea and Vomiting in Cancer Surgery: A New Frontier in Personalized Medicine Driven by Genome-Wide Association Studies

Indian Journal of Surgical Oncology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 30, 2024

Language: Английский

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