AI-Based Recipient Blood Type Matching Blood Transfusion Medical Device Design System

A. Sahu, Clarence Williams, S. Rajeev, Sharad Sharma
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引用次数: 0

Abstract

Acquisition of blood products is costly and blood transfusion increases the risk of adverse events in acute and delayed medical complications. Coupled with the increase in oncohaematological therapies and numerous types of major surgeries, the demand for blood products is growing year after year. In this paper, an AI-based favorable or unfavorable donor selection medical device is proposed. The paper charts out the medical device production implementation plan, identify data sources, forms AI-based device design structure, and medical device regulation standards for product quality identified. The authors predict that using AI (machine learning) end-to-end lifecycle of transfusion decision-making device as proposed will significantly reduce diagnostic, treatment protocol, and mismatch products errors.
基于人工智能的受体血型匹配输血医疗器械设计系统
获取血液制品成本高昂,输血增加了急性和延迟性医疗并发症中不良事件的风险。再加上血液肿瘤治疗的增加和许多类型的大手术,对血液制品的需求逐年增长。本文提出了一种基于人工智能的有利或不利供体选择医疗设备。制定医疗器械生产实施计划,确定数据来源,形成基于人工智能的器械设计结构,确定医疗器械产品质量监管标准。作者预测,使用人工智能(机器学习)端到端输血决策设备将显著减少诊断、治疗方案和错配产品的错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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