儿童医疗保健中的机器学习:当前趋势,挑战和未来方向
1Pediatric Critical Care Medicine, Cleveland Clinic Children's, 9500 Euclid Ave, Cleveland, OH 44195, USA.
Journal of clinical medicine
|February 13, 2025
概括
人工智能 (AI) 和机器学习 (ML) 在儿童医疗保健中显示出对诊断和治疗的前景. 克服数据限制和道德问题对于这些先进技术的广泛采用至关重要.
科学领域:
- 儿科医疗保健技术 儿童医疗保健技术
- 计算医学是一种计算医学.
- 生物医学信息学 生物医学信息学
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 正在通过预测和诊断能力彻底改变医疗保健.
- 儿科医疗保健面临着独特的障碍,包括数据稀缺,发育变异和道德考虑.
研究的目的:
- 审查当前的趋势,应用,挑战和儿童医疗保健中的ML的未来方向.
- 识别研究缺口和在儿科中推进ML的伦理考虑.
主要方法:
- 使用特定关键字对PubMed数据库进行系统的文献搜索.
- 审查精选的研究,以确定关键主题,方法,应用和挑战.
- 分析研究缺口和伦理考虑,提出未来的研究方向.
主要成果:
- 在儿科诊断支持,预后建模和治疗规划方面,ML显示出潜力.
- 应用包括早期败血症检测,增强的诊断成像和针对等疾病的个性化治疗.
- 挑战包括数据限制,伦理问题和模型通用性;联合学习和可解释AI (XAI) 是新兴的解决方案.
结论:
- ML对儿科医疗保健的挑战具有变革性的潜力.
- 解决数据多样性,道德准则和模型透明度对于有效实施至关重要.
- 未来的研究应该专注于提高数据的代表性,并确保在儿科护理中可靠的AI.
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