人工智能诊断乳腺癌准确率与专家相当
A computer programme can identify breast cancer from routine scans with greater accuracy than human experts, researchers said in what they hoped could prove a breakthrough in the fight against the global killer.
研究人员称，一种电脑程序可以通过常规扫描准确识别乳腺癌，而且它的准确率比人类专家的更高。他们希望该电脑程序可以在与乳腺癌这一全球杀手的斗争中取得突破。
Breast cancer is one of the most common cancers in women, with more than 2 million new diagnoses last year alone.
乳腺癌是女性最常罹患的癌症之一，仅去年一年就有200多万名新确诊的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者没有明显症状的时候，定期筛查对于发现疾病的早期症状至关重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英国，50岁以上的妇女被建议每三年做一次乳房X光检查，而其检查结果由两位单独的专家进行分析。
But interpreting the scans leaves room for error, and a small percentage of all mammograms either return a false positive - misdiagnosing a healthy patient as having cancer or false negative-missing the disease as it spreads.
但对扫描结果的解读也有可能出错，而且在所有乳房X光检查结果中，有一小部分要么是假阳性（将健康病人误诊为患有癌症），要么是假阴性（在疾病的传播过程中，没有诊断出疾病）。
Now researchers at Google Health have trained an artificial intelligence model to detect cancer in breast scans from thousands of women in Britain and the United States.
如今谷歌健康中心的研究人员已训练出一个人工智能模型，它可以通过乳房扫描来检测英国和美国数千名女性是否罹患癌症。
The images had already been reviewed by doctors in real life but unlike in a clinical setting, the machine had no patient history to inform its diagnoses.
实际上，医生们已经检查过这些图像了，不过与临床环境不同的是，这台机器不知道病人的病史，也没有据此来进行诊断。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
该研究团队发现，他们的人工智能模型可以通过扫描检查来预测乳腺癌，而且其准确度与放射科专家相当。
Further, the AI showed a reduction in the proportion of cases where cancer was incorrectly identified 5.7 percent in the US and 1.2 percent in Britain, respectively.
此外，该人工智能模型还显示，癌症被错误识别的比例有所下降，其中美国降低了5.7%，英国降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain.
美国和英国的漏诊率也分别降低了9.4%和2.7%。
"The earlier you identify a breast cancer the better it is for the patient," Dominic King, UK lead at Google Health, told AFP.
“越早发现乳腺癌，对病人越好，”谷歌健康中心英国分部负责人多米尼克•金告诉法新社。
"We think about this technology in a way that supports and enables an expert, or a patient ultimately, to get the best outcome from whatever diagnostics they've had."
“我们认为这项技术能够支持并最终使专家或患者从他们得到的诊断中获得最佳结果。”
A computer programme can identify breast cancer from routine scans with greater accuracy than human experts, researchers said in what they hoped could prove a breakthrough in the fight against the global killer.
研究人员称，一种电脑程序可以通过常规扫描准确识别乳腺癌，而且它的准确率比人类专家的更高。他们希望该电脑程序可以在与乳腺癌这一全球杀手的斗争中取得突破。
Breast cancer is one of the most common cancers in women, with more than 2 million new diagnoses last year alone.
乳腺癌是女性最常罹患的癌症之一，仅去年一年就有200多万名新确诊的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者没有明显症状的时候，定期筛查对于发现疾病的早期症状至关重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英国，50岁以上的妇女被建议每三年做一次乳房X光检查，而其检查结果由两位单独的专家进行分析。
But interpreting the scans leaves room for error, and a small percentage of all mammograms either return a false positive-misdiagnosing a healthy patient as having cancer or false negative - missing the disease as it spreads.
但对扫描结果的解读也有可能出错，而且在所有乳房X光检查结果中，有一小部分要么是假阳性（将健康病人误诊为患有癌症），要么是假阴性（在疾病的传播过程中，没有诊断出疾病）。
Now researchers at Google Health have trained an artificial intelligence model to detect cancer in breast scans from thousands of women in Britain and the United States.
如今谷歌健康中心的研究人员已训练出一个人工智能模型，它可以通过乳房扫描来检测英国和美国数千名女性是否罹患癌症。
The images had already been reviewed by doctors in real life but unlike in a clinical setting, the machine had no patient history to inform its diagnoses.
实际上，医生们已经检查过这些图像了，不过与临床环境不同的是，这台机器不知道病人的病史，也没有据此来进行诊断。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
该研究团队发现，他们的人工智能模型可以通过扫描检查来预测乳腺癌，而且其准确度与放射科专家相当。
Further, the AI showed a reduction in the proportion of cases where cancer was incorrectly identified 5.7 percent in the US and 1.2 percent in Britain, respectively.
此外，该人工智能模型还显示，癌症被错误识别的比例有所下降，其中美国降低了5.7%，英国降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain. 美国和英国的漏诊率也分别降低了9.4%和2.7%。
"The earlier you identify a breast cancer the better it is for the patient," Dominic King, UK lead at Google Health, told AFP.
“越早发现乳腺癌，对病人越好，”谷歌健康中心英国分部负责人多米尼克•金告诉法新社。
"We think about this technology in a way that supports and enables an expert, or a patient ultimately, to get the best outcome from whatever diagnostics they've had."
“我们认为这项技术能够支持并最终使专家或患者从他们得到的诊断中获得最佳结果。”
研究人员称，一种电脑程序可以通过常规扫描准确识别乳腺癌，而且它的准确率比人类专家的更高。他们希望该电脑程序可以在与乳腺癌这一全球杀手的斗争中取得突破。
Breast cancer is one of the most common cancers in women, with more than 2 million new diagnoses last year alone.
乳腺癌是女性最常罹患的癌症之一，仅去年一年就有200多万名新确诊的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者没有明显症状的时候，定期筛查对于发现疾病的早期症状至关重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英国，50岁以上的妇女被建议每三年做一次乳房X光检查，而其检查结果由两位单独的专家进行分析。
But interpreting the scans leaves room for error, and a small percentage of all mammograms either return a false positive - misdiagnosing a healthy patient as having cancer or false negative-missing the disease as it spreads.
但对扫描结果的解读也有可能出错，而且在所有乳房X光检查结果中，有一小部分要么是假阳性（将健康病人误诊为患有癌症），要么是假阴性（在疾病的传播过程中，没有诊断出疾病）。
Now researchers at Google Health have trained an artificial intelligence model to detect cancer in breast scans from thousands of women in Britain and the United States.
如今谷歌健康中心的研究人员已训练出一个人工智能模型，它可以通过乳房扫描来检测英国和美国数千名女性是否罹患癌症。
The images had already been reviewed by doctors in real life but unlike in a clinical setting, the machine had no patient history to inform its diagnoses.
实际上，医生们已经检查过这些图像了，不过与临床环境不同的是，这台机器不知道病人的病史，也没有据此来进行诊断。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
该研究团队发现，他们的人工智能模型可以通过扫描检查来预测乳腺癌，而且其准确度与放射科专家相当。
Further, the AI showed a reduction in the proportion of cases where cancer was incorrectly identified 5.7 percent in the US and 1.2 percent in Britain, respectively.
此外，该人工智能模型还显示，癌症被错误识别的比例有所下降，其中美国降低了5.7%，英国降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain.
美国和英国的漏诊率也分别降低了9.4%和2.7%。
"The earlier you identify a breast cancer the better it is for the patient," Dominic King, UK lead at Google Health, told AFP.
“越早发现乳腺癌，对病人越好，”谷歌健康中心英国分部负责人多米尼克•金告诉法新社。
"We think about this technology in a way that supports and enables an expert, or a patient ultimately, to get the best outcome from whatever diagnostics they've had."
“我们认为这项技术能够支持并最终使专家或患者从他们得到的诊断中获得最佳结果。”
A computer programme can identify breast cancer from routine scans with greater accuracy than human experts, researchers said in what they hoped could prove a breakthrough in the fight against the global killer.
研究人员称，一种电脑程序可以通过常规扫描准确识别乳腺癌，而且它的准确率比人类专家的更高。他们希望该电脑程序可以在与乳腺癌这一全球杀手的斗争中取得突破。
Breast cancer is one of the most common cancers in women, with more than 2 million new diagnoses last year alone.
乳腺癌是女性最常罹患的癌症之一，仅去年一年就有200多万名新确诊的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者没有明显症状的时候，定期筛查对于发现疾病的早期症状至关重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英国，50岁以上的妇女被建议每三年做一次乳房X光检查，而其检查结果由两位单独的专家进行分析。
But interpreting the scans leaves room for error, and a small percentage of all mammograms either return a false positive-misdiagnosing a healthy patient as having cancer or false negative - missing the disease as it spreads.
但对扫描结果的解读也有可能出错，而且在所有乳房X光检查结果中，有一小部分要么是假阳性（将健康病人误诊为患有癌症），要么是假阴性（在疾病的传播过程中，没有诊断出疾病）。
Now researchers at Google Health have trained an artificial intelligence model to detect cancer in breast scans from thousands of women in Britain and the United States.
如今谷歌健康中心的研究人员已训练出一个人工智能模型，它可以通过乳房扫描来检测英国和美国数千名女性是否罹患癌症。
The images had already been reviewed by doctors in real life but unlike in a clinical setting, the machine had no patient history to inform its diagnoses.
实际上，医生们已经检查过这些图像了，不过与临床环境不同的是，这台机器不知道病人的病史，也没有据此来进行诊断。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
该研究团队发现，他们的人工智能模型可以通过扫描检查来预测乳腺癌，而且其准确度与放射科专家相当。
Further, the AI showed a reduction in the proportion of cases where cancer was incorrectly identified 5.7 percent in the US and 1.2 percent in Britain, respectively.
此外，该人工智能模型还显示，癌症被错误识别的比例有所下降，其中美国降低了5.7%，英国降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain. 美国和英国的漏诊率也分别降低了9.4%和2.7%。
"The earlier you identify a breast cancer the better it is for the patient," Dominic King, UK lead at Google Health, told AFP.
“越早发现乳腺癌，对病人越好，”谷歌健康中心英国分部负责人多米尼克•金告诉法新社。
"We think about this technology in a way that supports and enables an expert, or a patient ultimately, to get the best outcome from whatever diagnostics they've had."
“我们认为这项技术能够支持并最终使专家或患者从他们得到的诊断中获得最佳结果。”
