用人工智能,机器学习和深度学习改变临床病毒学:全面的审查和前景
Abhishek Padhi1, Ashwini Agarwal1, Shailendra K Saxena2
1Department of Microbiology, All India Institute of Medical Sciences, Rajkot, Gujarat 360110 India.
Virusdisease
|October 2, 2023
概括
人工智能 (AI) 和机器学习正在彻底改变临床病毒学,提高诊断和药物发现. 解决数据安全和偏见等挑战是病毒研究和患者护理未来进步的关键.
科学领域:
- 临床病毒学 临床病毒学
- 计算生物学是一种计算生物学.
- 生物信息学是一种生物信息学.
背景情况:
- 技术进步对于临床病毒学的进步至关重要.
- 人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 正在成为强大的工具.
研究的目的:
- 审查AI,ML和DL在病毒学研究和实践中的整合和影响.
- 突出诊断,治疗和流行病学的应用.
- 讨论挑战,并为负责任的实施提出解决方案.
主要方法:
- 对AI/ML/DL在病毒学中的应用进行了全面的文献综述.
- 对展示算法能力的案例研究进行分析.
- 讨论包括数据安全,偏见和道德在内的挑战.
主要成果:
- AI/ML/DL显著提高了诊断的准确性和速度.
- 这些技术加速了病毒基因组测序和药物发现.
- 对病毒爆发的预测洞察力得到了增强.
- 关键的挑战包括数据安全,算法偏见和道德考虑.
结论:
- 人工智能驱动的工具正在改变病毒学,导致更加主动和个性化的患者护理.
- 跨学科的合作对于克服实施挑战至关重要.
- 人工智能和病毒学之间的共生关系预计将为未来的突破提供帮助.
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