Progressive role of artificial intelligence in treatment decision-making in the field of medical oncology DOI Creative Commons
Archana Reddy Bongurala, Dhaval Save,

Ankit Virmani

et al.

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: Feb. 13, 2025

This article explores the role of artificial intelligence (AI) in medical oncology, emphasizing its impact on treatment decision-making for adult and pediatric cancer care. AI applications, including advanced imaging, drug discovery, clinical decision support systems, enhance precision, personalization, efficiency. Pediatric oncology benefits from improved diagnostics, risk stratification, targeted therapies, despite unique challenges. AI-driven personalized medicine optimizes strategies, improving patient outcomes reducing costs. Ethical considerations, such as data privacy, algorithmic bias, explainability, remain critical responsible integration. Future advancements, explainable quantum computing, promise to redefine care through data-driven insights.

Language: Английский

Revolutionizing Prostate Cancer Therapy: Artificial intelligence – based Nanocarriers for Precision Diagnosis and Treatment DOI
Moein Shirzad,

Afsaneh Salahvarzi,

Sobia Razzaq

et al.

Critical Reviews in Oncology/Hematology, Journal Year: 2025, Volume and Issue: unknown, P. 104653 - 104653

Published: Feb. 1, 2025

Language: Английский

Citations

3

Predicting intermediate-risk prostate cancer using machine learning DOI
Miroslav Stojadinović, Milorad Stojadinović, Slobodan Јаnkovic

et al.

International Urology and Nephrology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 3, 2025

Language: Английский

Citations

1

Analysis of incidental prostate acinar adenocarcinoma: a single-center retrospective study DOI Open Access
Berna Eriten, Meryem Yüvrük, Mihriban Gürbüzel

et al.

The European Research Journal, Journal Year: 2025, Volume and Issue: 11(2), P. 319 - 327

Published: Jan. 9, 2025

Objective: Our study was conducted in a single center to evaluate the characteristics of prostate acinar adenocarcinoma. Methods: A retrospective archive search between January 1, 2018 and September 2024, 900 transurethral resection (TUR) 127 open prostatectomy materials were examined. total 43 TUR 9 found have prostatic Results: The ages patients 51-90. Gleason scores ranged from 3+3:6 5+5:10. In immunohistochemical analyses, Alpha methylacyl CoA racemase (AMACR) positivity p63 negativity prominent as characteristic findings. Lymphovascular invasion rarely observed, while perineural detected more frequently. Conclusions: importance histopathological features determining diagnostic prognostic factors adenocarcinoma investigated our study. This may contribute literature on cancer treatment strategies provide contributions for future research.

Language: Английский

Citations

0

Digital Pathology Allows for Global Second Opinions for Urologic Malignancies DOI Creative Commons
Daniel Shepherd, Jennifer Gordetsky

Current Urology Reports, Journal Year: 2025, Volume and Issue: 26(1)

Published: Feb. 8, 2025

Digital pathology, the use of digital images for histopathologic diagnosis, is transforming practice pathology. This review discusses ability pathology to assist with second opinions challenging cases in genitourinary worldwide. While traditional limited by physical hardware such as microscopes and glass slides, creates opportunities rapid sharing diagnostic materials colleagues experts technology can greatly facilitate from low-resource areas where services or subspecialty expertise are not available. As incidence kidney, prostate, testicular cancer continues increase both high-income developing countries, may be solution expert diagnosing urologic disease

Language: Английский

Citations

0

Progressive role of artificial intelligence in treatment decision-making in the field of medical oncology DOI Creative Commons
Archana Reddy Bongurala, Dhaval Save,

Ankit Virmani

et al.

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: Feb. 13, 2025

This article explores the role of artificial intelligence (AI) in medical oncology, emphasizing its impact on treatment decision-making for adult and pediatric cancer care. AI applications, including advanced imaging, drug discovery, clinical decision support systems, enhance precision, personalization, efficiency. Pediatric oncology benefits from improved diagnostics, risk stratification, targeted therapies, despite unique challenges. AI-driven personalized medicine optimizes strategies, improving patient outcomes reducing costs. Ethical considerations, such as data privacy, algorithmic bias, explainability, remain critical responsible integration. Future advancements, explainable quantum computing, promise to redefine care through data-driven insights.

Language: Английский

Citations

0