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| http://dx.doi.org/10.3389/fmicb.2023.1284838 | DOI Listing |
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Harnessing machine learning to predict prostate cancer survival: a review.
Front Oncol
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Department of Urology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
The prediction of survival outcomes is a key factor in making decisions for prostate cancer (PCa) treatment. Advances in computer-based technologies have increased the role of machine learning (ML) methods in predicting cancer prognosis. Due to the various effective treatments available for each non-linear landscape of PCa, the integration of ML can help offer tailored treatment strategies and precision medicine approaches, thus improving survival in patients with PCa.
View Article and Find Full Text PDFHarnessing the AI/ML in Drug and Biological Products Discovery and Development: The Regulatory Perspective.
Pharmaceuticals (Basel)
January 2025
College of Pharmacy, University of Illinois, Chicago, IL 60612, USA.
Artificial Intelligence (AI) has the disruptive potential to transform patients' lives via innovations in pharmaceutical sciences, drug development, clinical trials, and manufacturing. However, it presents significant challenges, ethical concerns, and risks across sectors and societies. AI's rapid advancement has revealed regulatory gaps as existing public policies struggle to keep pace with the challenges posed by these emerging technologies.
View Article and Find Full Text PDFArtificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.
J Clin Med
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Department of Neurosurgery, "Carol Davila" University of Medicine and Pharmacy, 020021 Bucharest, Romania.
The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding of the brain, unlocking new possibilities in research, diagnosis, and therapy. This review explores how AI's cutting-edge algorithms-ranging from deep learning to neuromorphic computing-are revolutionizing neuroscience by enabling the analysis of complex neural datasets, from neuroimaging and electrophysiology to genomic profiling. These advancements are transforming the early detection of neurological disorders, enhancing brain-computer interfaces, and driving personalized medicine, paving the way for more precise and adaptive treatments.
View Article and Find Full Text PDFHarnessing Artificial Intelligence to Enhance Global Breast Cancer Care: A Scoping Review of Applications, Outcomes, and Challenges.
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Background: In recent years, Artificial Intelligence (AI) has shown transformative potential in advancing breast cancer care globally. This scoping review seeks to provide a comprehensive overview of AI applications in breast cancer care, examining how they could reshape diagnosis, treatment, and management on a worldwide scale and discussing both the benefits and challenges associated with their adoption.
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Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis.
Biomedicines
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School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Unlabelled: Japanese Encephalitis (JE) is the leading cause of viral encephalitis in regions with endemic Japanese Encephalitis Virus (JEV) infections.
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Discussion: As climate change continues to impact mosquito population growth patterns, more regions will be affected by mosquito-borne diseases, including JE.
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