کاربردهای هوش مصنوعی در بهبود تجزیه و تحلیل داده های پزشکی و تصمیم گیری، یک مرور نظام مند
کد: G-1712
نویسندگان: Mehrdad Nourizadeh *, Mobina Hoseinzadeh ℗, Saeed Mohammadzadeh Mounesyar, Yalda Jalali, Zeynab Rasouli, Mehdi Amirhooshangi
زمان بندی: زمان بندی نشده!
برچسب: پردازش سیگنال های پزشکی
دانلود: دانلود پوستر
خلاصه مقاله:
خلاصه مقاله
Background and Aims: Artificial Intelligence (AI) is progressively utilized in healthcare to enhance data processing, facilitate diagnoses, and assist clinical decisions. Given the surge in medical data, AI can streamline information management, thereby improving patient care. This review aims to examine the application of AI in healthcare data processing and decision- making, promoting greater accuracy and reliability in medical systems. Method: This review adhered to standard systematic review protocols, conducting searches across PubMed, Scopus, Embase, and Web of Science databases. Articles published within the last five years were selected, emphasizing keywords like “Artificial Intelligence,” “Machine Learning,” “Medical Data Analysis,” “Clinical Decision Support,” and “Digital Health.” Studies employing AI for medical data processing, clinical decision support, or prediction accuracy enhancement were prioritized. A total of 15 studies were chosen from 412 records screened based on these criteria. Results: From the review of 412 records, fifteen studies were identified. Various AI techniques, such as foundational machine learning models, text analysis tools, and diagnostic algorithms, were implemented to boost data analysis and decision- making. Convolutional Neural Networks (CNNs) demonstrated accuracy rates exceeding 85% in analyzing medical images. Additionally, some studies employed Natural Language Processing (NLP) to enhance the understanding of patient records, thus improving clinical support systems' accuracy. Foundational machine learning models were also utilized to forecast patient outcomes and refine treatment plans. Conclusion: AI technologies are increasingly leveraged for processing medical data, aiding clinical decisions, and predicting patient care outcomes. Although these technologies hold great promise, further research is essential to ensure their reliability and effectiveness across diverse healthcare environments.
کلمات کلیدی
Artificial Intelligence,Clinical Decision,Data Analysis,Decision-making,NLP,Systematic Review
