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Integrating AI into Cancer Immunotherapy-A Narrative Review of Current Applications and Future Directions.
Diseases
January 2025
Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, Canterbury, Kent CT1 1QU, UK.
Background: Cancer remains a leading cause of morbidity and mortality worldwide. Traditional treatments like chemotherapy and radiation often result in significant side effects and varied patient outcomes. Immunotherapy has emerged as a promising alternative, harnessing the immune system to target cancer cells.
View Article and Find Full Text PDFFibro-osseous lesions of the sinonasal tract: a contemporary review.
Curr Opin Otolaryngol Head Neck Surg
February 2025
Department of Otolaryngology - Head & Neck Surgery, University of Florida, Gainesville, Florida, USA.
Purpose Of Review: Fibro-osseous lesions (FOL) are benign, slow-growing lesions that are often incidentally discovered in the sinonasal cavity. They may necessitate surgical resection in patients with postobstructive sinusitis, or in cases of cranial nerve and orbital compression. We examine the recent advancements in otolaryngology relating to diagnostic characteristics and treatments for FOL, with emphasis on new technologies to improve outcomes and reduce recurrence.
View Article and Find Full Text PDFHarnessing magnetism: evaluation of safety, tolerance and feasibility of magnetic kidney stone retrieval in vivo in porcine models.
Urolithiasis
December 2024
Division of Medicinal Chemistry, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstr. 6, 8010, Graz, Austria.
The primary objective of urolithiasis therapy is complete stone removal and highest stone-clearance rates possible to minimize recurrence. A novel approach that employs a magnetic suspension and a magnetic probe for the passive collection and removal of small residual fragments was developed. This study assessed the feasibility of this system in porcine models.
View Article and Find Full Text PDFAchieving high-fidelity image transmission through turbid media is a significant challenge facing both the AI and photonic/optical communities. While this capability holds promise for a variety of applications, including data transfer, neural endoscopy, and multi-mode optical fiber-based imaging, conventional deep learning methods struggle to capture the nuances of light propagation, leading to weak generalization and limited reconstruction performance. To address this limitation, we investigated the non-locality present in the reconstructed images and discovered that conventional deep learning methods rely on specific features extracted from the training dataset rather than meticulously reconstructing each pixel.
View Article and Find Full Text PDFComparative bibliometric analysis of artificial intelligence-assisted polyp diagnosis and AI-assisted digestive endoscopy: trends and growth in AI gastroenterology (2003-2023).
Front Med (Lausanne)
September 2024
Medical School, Tianjin University, Tianjin, China.
Introduction: Artificial intelligence is already widely utilized in gastroenterology. This study aims to comprehensively evaluate the research hotspots and development trends within the field of AI in gastroenterology by employing bibliometric techniques to scrutinize geographical distribution, authorship, affiliated institutions, keyword usage, references, and other pertinent data contained within relevant publications.
Methods: This investigation compiled all pertinent publications related to artificial intelligence in the context of gastrointestinal polyps and digestive endoscopy from 2003 to 2023 within the Web of Science Core Collection database.
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