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Unraveling the Invisible: Topological Data Analysis as the New Frontier in Radiology's Diagnostic Arsenal.
Tomography
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Department of Radiology, University of Padova, 35127 Padova, Italy.
This commentary examines Topological Data Analysis (TDA) in radiology imaging, highlighting its revolutionary potential in medical image interpretation. TDA, which is grounded in mathematical topology, provides novel insights into complex, high-dimensional radiological data through persistent homology and topological features. We explore TDA's applications across medical imaging domains, including tumor characterization, cardiovascular imaging, and COVID-19 detection, where it demonstrates 15-20% improvements over traditional methods.
View Article and Find Full Text PDFAn analysis of the methodology used by the authors of the commented article is presented and errors related to data preparation are pointed out.
View Article and Find Full Text PDFPre-Radiation Targeted Therapy for Highly Selected Patients with Newly Diagnosed Glioblastoma: New Tricks for an Old Dog?
Neuro Oncol
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Division of Neuro-Oncology, Department of Neurology, and the Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians & Surgeons and New York-Presbyterian New York, NY, USA.
Transforming Healthcare: Artificial Intelligence (AI) Applications in Medical Imaging and Drug Response Prediction.
Genome Integr
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Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Artificial intelligence (AI) offers a broad range of enhancements in medicine. Machine learning and deep learning techniques have shown significant potential in improving diagnosis and treatment outcomes, from assisting clinicians in diagnosing medical images to ascertaining effective drugs for a specific disease. Despite the prospective benefits, adopting AI in clinical settings requires careful consideration, particularly concerning data generalisation and model explainability.
View Article and Find Full Text PDFImproving eating disorder care for underserved groups: a lived experience and quality improvement perspective.
J Eat Disord
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, London, UK.
Improvements to eating disorder (ED) care are urgently needed in the United Kingdom (UK) and around the world. Informed by my lived experiences, independent research, and involvement in the underappreciated field of quality improvement (QI), I have written this article to offer ideas on how to improve individuals' access to and experiences of ED care. As I live in the UK, my lived and QI experiences are of the UK's National Health Service (NHS).
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