Artificial intelligence changing the future of healthcare diagnostics

Q3 Biochemistry, Genetics and Molecular Biology
Vaishnavi Mishra, Sarita Ugemuge, Yugeshwari R. Tiwade
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引用次数: 1

Abstract

Artificial intelligence (AI) is a computer’s capacity to carry out operations like speech and image recognition and decision-making that ordinarily require human intelligence. Healthcare is using AI to automate tasks such as medical image analysis and diagnosis that require high precision and accuracy. The healthcare industry is significantly impacted by the rapid development of machine learning algorithms, which are frequently implemented using deep learning, as well as the growth of digital data and computing power supported by improvements in hardware technologies. Significant progress has been made in the field of artificial intelligence in recent years and is now widely used in healthcare to automate a variety of tasks, which require a high degree of accuracy and precision. The creation of machine learning algorithms, which can learn from data and make predictions based on that learning, has made it possible to use AI in healthcare. Neural networks are used in deep learning, a subfield of machine learning, to simulate how the human brain functions. Crucial advances have been made in clinical decision support, drug discovery, and medical imaging. Furthermore, the rapid development of hardware technologies, such as graphics processing units, has allowed AI systems to process enormous amounts of data quickly and accurately. Due to this, AI-based tools and platforms can help healthcare professionals with tasks such as patient monitoring, disease diagnosis, and treatment planning.
人工智能改变医疗诊断的未来
人工智能(AI)是一种计算机执行语音、图像识别和决策等通常需要人类智能的操作的能力。医疗保健正在使用人工智能来自动化医疗图像分析和诊断等需要高精度和准确性的任务。医疗保健行业受到机器学习算法的快速发展的重大影响,机器学习算法经常使用深度学习来实现,以及硬件技术改进所支持的数字数据和计算能力的增长。近年来,人工智能领域取得了重大进展,目前已广泛应用于医疗保健领域,以实现各种任务的自动化,这些任务需要高度的准确性和准确性。机器学习算法的创建,可以从数据中学习并根据学习做出预测,使人工智能在医疗保健中的应用成为可能。神经网络用于机器学习的子领域深度学习,以模拟人脑的功能。在临床决策支持、药物发现和医学成像方面取得了至关重要的进展。此外,图形处理单元等硬件技术的快速发展使人工智能系统能够快速准确地处理大量数据。因此,基于人工智能的工具和平台可以帮助医疗保健专业人员完成患者监测、疾病诊断和治疗计划等任务。
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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来源期刊
Journal of Cellular Biotechnology
Journal of Cellular Biotechnology Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
0.70
自引率
0.00%
发文量
13
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