放射学和机器学习在早期检测口腔潜在恶性疾病
Ashwini Dhopte1, Vikas Singh2, J Sophia J Priya3
1Department of Oral Medicine and Radiology, Chhattisgarh Dental College and Research Institute, Rajnandgaon, Chhattisgarh, India.
Journal of pharmacy & bioallied sciences
|January 12, 2026
概括
对口腔潜在恶性疾病 (OPMDs) 的早期检测至关重要. 放射学和机器学习 (ML) 在提高OPMD检测的诊断准确度和生存率方面表现有前途.
科学领域:
- 口服药是一种口服药.
- 放射学 放射学是一门学科.
- 人工智能的人工智能是人工智能.
背景情况:
- 口腔潜在恶性疾病 (OPMDs) 具有进展到口腔状细胞癌 (OSCC) 的显著风险.
- 早期诊断OPMD对于改善患者的治疗结果和生存率至关重要.
- 传统的诊断方法在准确性和及时性上可能受到限制.
研究的目的:
- 审查放射学和机器学习 (ML) 在OPMDs早期检测中的应用.
- 突出这些技术在提高诊断准确度方面的潜力.
- 讨论当前的研究,挑战和该领域的未来方向.
主要方法:
- 使用放射学从医学图像中提取定量特征.
- 机器学习算法的应用用于模式识别和预测建模.
- 分析与OPMD相关的各种成像模式和数据处理技术.
主要成果:
- 放射学和ML在提高OPMD检测的准确性方面显示出显著的潜力.
- 这些技术可以帮助识别暗示恶性转变的微妙变化.
- 定量成像分析为风险分层提供了新的途径.
结论:
- 放射学和机器学习是早期发现和诊断OPMDs的有希望的工具.
- 需要进一步的研究和验证才能充分将这些技术纳入临床实践.
- 人工智能和成像技术的进步是改善OPMD管理和患者生存的关键.
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