Examples of using 预测癌症 in Chinese and their translations into English
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人工智能有助于预测癌症症状，计划治疗.
Artificial intelligence helps predict cancer symptoms, plan treatment.预测癌症风险和管理医疗.
Predicting cancer risk and managing care.如果这种趋势继续下去，他们预测癌症可能会变成本世纪后期世界范围内的主要死亡原因。
If the trend continues, they predict cancer could become the leading cause of death worldwide later in this century.然而，健康专家预测癌症将成为女性死亡的一号杀手。
However, health experts predict cancer will become the number one reason for female mortality.她说，通常情况下，医生和研究人员在预测癌症预后时，只关注临床因素，例如肿瘤的发展阶段。
Normally, doctors and researchers look at only clinical factors, such as the stage of a tumor,when predicting cancer prognosis, she said.Combinations with other parts of speech
我们也尝试着鉴别出可以预测癌症演化的生物标记，并为这些患者提供早期的治疗性介入。
We also try to identify biomarkers that predict cancer progression and provide these patients with early therapeutic interventions.”.这些变化未被早期的分析方法检测到，可能用于鉴定出预测癌症患者存活的新型生物标志物和新的治疗靶标。
These alterations, previously undetected by earlier methods of analysis,may identify novel biomarkers for predicting cancer patient survival and new targets for therapies.如果这种趋势继续下去，他们预测癌症可能会变成本世纪后期世界范围内的主要死亡原因。
If thetrendcontinues, they predict cancer could become the leading cause of death worldwide later in this century.通过向我们展望未来，我们可以利用这种人工智能工具在早期阶段进行干预，预测癌症的下一步行动。
By giving us a peek into the future, we could potentially use thisAI tool to intervene at an earlier stage, predicting cancer's next move.我们还试图识别预测癌症进展的生物标志物，为这些患者提供早期治疗干预。
We also try to identify biomarkers that predict cancer progression and provide these patients with early therapeutic interventions.”.据悉，将来该设备还有望用于预测癌症风险。
In addition,it is believed that the novel device will be used for predicting cancer risk in the future.Jamieson说，“基于这项研究，我们认为检测ADAR1活性将是预测癌症发展的一个重要指标。
Based on this research, we believe that detectingADAR1 activity will be important for predicting cancer progression.将微生物群分析添加到侵袭性结肠直肠癌的危险因素中，使得预测癌症的能力提高了5倍。
Adding microbiome analysis 最终，这个神经网络就可以做一个病理学家所做的工作：检查身体组织的图像来预测癌症。
Eventually, this neural network will be ready 然后，他们使用NVIDIAGPU和cuDNN加速的TensorFlow深度学习框架，训练卷积神经网络根据乳腺影像预测癌症诊断。
Then, using NVIDIA GPUs with the cuDNN-accelerated TensorFlow deep learning framework,they trained a convolutional neural network to predict cancer diagnoses based on breast imaging.最终，这个神经网络将准备好做病理学家通常做的事情：检查组织图像以预测癌症。
Eventually, this neural network will be ready 埃克塞特小组专门确定哪些症状可以预测癌症，以辅助早期诊断，但是他们的大部分工作都围绕着已知的风险标记进行量化。
The Exeter group specialises in identifying which symptoms predict cancer to aid early diagnosis, however most of their work centres around quantifying known risk markers.埃克塞特小组专门肯定哪些症状能够预测癌症，以帮助早期诊断，但是他们的大部分工作都围绕着已知的危险标志进行量化。
The Exeter group specialises in identifying which symptoms predict cancer to aid early diagnosis, however most of their work centres around quantifying known risk markers.多年来，已经提出了许多不同的肿瘤生长的数学模型，但是确定哪一个在预测癌症进展中最准确是一个挑战。
Different mathematical models of tumor growth have been proposed over the years,but determining which is most accurate at predicting cancer progression is a challenge.预测癌症患者的预期寿命已经够困难的了。
这有助于医生预测癌症可能增长和扩散的速度。
结果表明，该团队为预测癌症生存结果设计了强大的模型。
科学家们已经使用人工智能来预测癌症将如何发展和进化。
科学家们已经使用人工智能来预测癌症将如何发展和进化。
Scientists have used AI to predict how cancers will progress and evolve.研究人员下一步将开发人工智能模型，以更好地预测癌症风险。
The researchers' next step willbe 级别是用来帮助预测癌症的生长和扩散可能性的许多因素之一。
Grade is one of the many factors that are used to help predict how likely a cancer is to grow and spread.检测细胞中DNA损伤可以预测癌症是否会发展，但是对这种损伤的测试灵敏度有限。
The detection of DNA damage in cells can predict whether cancer will develop, but tests for this kind of damage have limited sensitivity.几年前，Manalis及其同事着手调整这项技术以预测癌症药物如何影响肿瘤细胞生长。
A few years ago,Manalis and colleagues set out 
