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甲状腺癌的进展和挑战:基因调节器的相互作用,向疗法和人工智能驱动的方法
Srinjan Bhattacharya1, Rahul Kumar Mahato1, Satwinder Singh2
1Laboratory of Translational Medicine and Nanotherapeutics, Department of Human Genetics and Molecular Medicine, School of Health Sciences, Central University of Punjab, Bathinda 151401, Punjab, India.
甲状腺癌的发病率正在上升,特别是在女性中. 这篇评论探讨了基因,表观遗传和RNA因素,以及人工智能和机器学习,以更好地治疗甲状腺癌和改善治疗结果.
科学领域:
- 在瘤学瘤学.
- 遗传学 是一个遗传学.
- 生物信息学是一种生物信息学.
背景情况:
- 在全球范围内,甲状腺癌的发病率正在增加,特别是在女性中.
- 虽然差异化甲状腺癌有标准的治疗方法,但更罕见的类型,如厌塑性甲状腺癌,需要专门的治疗方法.
- 了解遗传,表观遗传和非编码RNA因子的复杂相互作用对于治疗甲状腺癌至关重要.
研究的目的:
- 审查甲状腺癌的基本调节器,包括遗传,表观遗传和非编码RNA因素.
- 探索这些因素在瘤形成中的相互作用.
- 提供当前治疗干预措施的概述,以及人工智能和机器学习在甲状腺癌中的潜力.
主要方法:
- 在甲状腺癌中对遗传,表观遗传和非编码RNA因素的文献综述.
- 分析当前的药物和非药物治疗策略.
- 在甲状腺癌研究和临床实践中探索人工智能和机器学习应用.
主要成果:
- 遗传,表观遗传和非编码RNA因素显著影响甲状腺癌的发展和进展.
- 表观遗传修饰和非编码RNA在基因表达和瘤发生中起着关键作用.
- 人工智能和机器学习显示出预测治疗结果和个性化治疗的前景.
结论:
- 对甲状腺癌的分子基础有全面的了解,对于有效治疗至关重要.
- 人工智能和机器学习等新兴技术为改善诊断和治疗策略提供了新的途径.
- 整合分子洞察力和先进分析的个性化治疗方法是甲状腺癌护理的未来.
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