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Towards Enhanced Accuracy in Medical Diagnostics -- A Technique Utilizing Statistical and Clinical Data Analysis in the Context of Ultrasound Images

机译:致力于提高医疗诊断的准确性-一种在超声图像背景下利用统计和临床数据分析的技术

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Biomedical imaging remains as a critical thrust area in the healthcare domain with colossal challenges and opportunities associated with analyzing and intelligent utilization of the enormous amounts of data. This research explores the domain of ultrasound images from the perspective of statistical and clinical data modeling and analytics. We propose a technique towards enhancing diagnostic accuracy of the current state and prediction of future states in the context of anomalous/cancerous tissue growth. The proposed technique utilizes both statistical and clinical data associated with ultrasound scans of the cancerous tissue in developing a probabilistic data model towards enhanced inferences with respect to current state of disease and future estimates of survivability. Preliminary evaluation of the proposed technique shows that combining statistical parametric estimates with clinical rule based prediction yields a more accurate model of disease diagnosis. One of the implications of the proposed technique is the potential of practicing evidence based medicine rooted in factual statistical and clinical data thereby reducing variability with respect to diagnostics and corresponding treatment.
机译:生物医学成像仍然是医疗保健领域的重要推力领域,面临着与分析和智能利用大量数据相关的巨大挑战和机遇。这项研究从统计和临床数据建模与分析的角度探讨了超声图像的领域。我们提出了一种在异常/癌变组织生长的背景下提高当前状态的诊断准确性和预测未来状态的技术。所提出的技术在开发概率数据模型时利用了与癌组织超声扫描相关的统计数据和临床数据,以针对疾病的当前状态和未来的生存能力做出增强的推断。对所提出技术的初步评估表明,将统计参数估计与基于临床规则的预测相结合,可以得出更准确的疾病诊断模型。所提出的技术的含义之一是实践基于事实统计和临床数据的循证医学的潜力,从而减少了诊断和相应治疗的可变性。

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