مروری جامع بر تلفیق آسیبشناسی دیجیتال و میکروبیوم با بهرهگیری از هوش مصنوعی در تشخیص و پیشآگاهی بیماریها
کد: G-1866
نویسندگان: Masume Molavi * ℗, Fateme Molavi, Amin Hedayati Moghaddam
زمان بندی: زمان بندی نشده!
برچسب: سیستم های تصمیم یار بالینی
دانلود: دانلود پوستر
خلاصه مقاله:
خلاصه مقاله
Background and Aims: Combining digital pathology with microbiome research is changing the way we understand and treat diseases. Advanced imaging and artificial intelligence (AI) methods in digital pathology reveal detailed tissue structures, while microbiome studies explore how microbes affect health. This review gathers recent progress, obstacles, and future prospects in linking tissue imaging with microbiome data using AI. It suggests that this approach could greatly improve both diagnosis and prognosis. Methods: A detailed literature search was performed using keywords such as "digital pathology AND microbiome", "AI in pathology AND microbial ecology," and "multimodal AI AND microbiome" across databases, focusing on work that combines digital pathology with microbiome analysis via AI. Results: Significant improvements have been noted in digital pathology, with AI models, especially neural networks, achieving high accuracy in disease detection from tissue samples. Microbiome research has identified specific microbial patterns linked to illnesses such as colorectal cancer and inflammatory bowel disease. When data from digital pathology and microbiome studies are merged using AI, new biomarkers have been found and the prediction of disease outcomes has improved. For example, certain bacteria within tumor environments have been associated with cancer prognosis. Nonetheless, issues like data uniformity, clarity in AI model decisions, and privacy concerns still need to be addressed. Conclusion: The merging of digital pathology and microbiome research through AI offers promising avenues for personalized medicine. Overcoming technical, clinical, and ethical challenges is essential for fully harnessing this potential. Future work should focus on developing reliable multimodal AI models, establishing standardized datasets, and investigating new applications for disease diagnosis and treatment. Collaboration among experts in pathology, microbiology, and AI is key to driving this interdisciplinary field forward.
کلمات کلیدی
Digital Pathology, Artificial Intelligence, Microbiome
