使用人工智能和机器学习方法来增强癌症治疗和药物发现:一个叙事回顾
Khurram Shahzad1, Marwan Abu-Zanona2, Bassam Mohammad Elzaghmouri3
1HIESS Department, Hamdard University, Karachi-Pakistan.
Journal of Ayub Medical College, Abbottabad : JAMC
|November 25, 2024
概括
人工智能 (AI) 和机器学习加速了抗癌药物的发现和合成. 这些技术提高了药物设计和查,为更有效的癌症疗法和更少副作用铺平了道路.
科学领域:
- 在瘤学瘤学.
- 计算化学计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 在过去的十年中,人工智能和机器学习对抗癌药物开发产生了重大影响.
- 这些技术加速了新型抗癌化合物的识别和合成.
研究的目的:
- 审查基于人工智能的技术在抗癌药物开发中的应用.
- 突出人工智能对癌症研究和治疗的贡献.
主要方法:
- 对人工智能在抗癌药物开发中的应用进行叙述性审查.
- 检查机器学习技术在药物设计和选中.
主要成果:
- 人工智能增强了蛋白质相互作用网络分析,药物标预测,结合部位预测和虚拟查.
- 机器学习改善了药物设计和选,使多目标药物开发能够减少副作用.
- 人工智能的局限性包括数据依赖性和狭窄的可解释性;可解释的人工智能模型是未来的方向.
结论:
- 人工智能是一种强大的技术,即将彻底改变抗癌疗法开发.
- 人工智能有可能加速,降低成本并提高抗癌药物开发的有效性.
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