人工智能診斷乳腺癌準確率與專家相當
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.
研究人員稱，一種電腦程序可以通過常規(guī)掃描準確識別乳腺癌，而且它的準確率比人類專家的更高。他們希望該電腦程序可以在與乳腺癌這一全球殺手的斗爭中取得突破。
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癥之一，僅去年一年就有200多萬名新確診的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者沒有明顯癥狀的時候，定期篩查對于發(fā)現疾病的早期癥狀至關重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英國，50歲以上的婦女被建議每三年做一次乳房X光檢查，而其檢查結果由兩位單獨的專家進行分析。
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.
但對掃描結果的解讀也有可能出錯，而且在所有乳房X光檢查結果中，有一小部分要么是假陽性（將健康病人誤診為患有癌癥），要么是假陰性（在疾病的傳播過程中，沒有診斷出疾病）。
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員已訓練出一個人工智能模型，它可以通過乳房掃描來檢測英國和美國數千名女性是否罹患癌癥。
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.
實際上，醫(yī)生們已經檢查過這些圖像了，不過與臨床環(huán)境不同的是，這臺機器不知道病人的病史，也沒有據此來進行診斷。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
該研究團隊發(fā)現，他們的人工智能模型可以通過掃描檢查來預測乳腺癌，而且其準確度與放射科專家相當。
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，該人工智能模型還顯示，癌癥被錯誤識別的比例有所下降，其中美國降低了5.7%，英國降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain.
美國和英國的漏診率也分別降低了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.
“越早發(fā)現乳腺癌，對病人越好，”谷歌健康中心英國分部負責人多米尼克•金告訴法新社。
"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."
“我們認為這項技術能夠支持并最終使專家或患者從他們得到的診斷中獲得最佳結果。”
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.
研究人員稱，一種電腦程序可以通過常規(guī)掃描準確識別乳腺癌，而且它的準確率比人類專家的更高。他們希望該電腦程序可以在與乳腺癌這一全球殺手的斗爭中取得突破。
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癥之一，僅去年一年就有200多萬名新確診的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者沒有明顯癥狀的時候，定期篩查對于發(fā)現疾病的早期癥狀至關重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英國，50歲以上的婦女被建議每三年做一次乳房X光檢查，而其檢查結果由兩位單獨的專家進行分析。
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.
但對掃描結果的解讀也有可能出錯，而且在所有乳房X光檢查結果中，有一小部分要么是假陽性（將健康病人誤診為患有癌癥），要么是假陰性（在疾病的傳播過程中，沒有診斷出疾?。?。
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員已訓練出一個人工智能模型，它可以通過乳房掃描來檢測英國和美國數千名女性是否罹患癌癥。
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.
實際上，醫(yī)生們已經檢查過這些圖像了，不過與臨床環(huán)境不同的是，這臺機器不知道病人的病史，也沒有據此來進行診斷。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
該研究團隊發(fā)現，他們的人工智能模型可以通過掃描檢查來預測乳腺癌，而且其準確度與放射科專家相當。
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，該人工智能模型還顯示，癌癥被錯誤識別的比例有所下降，其中美國降低了5.7%，英國降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain. 美國和英國的漏診率也分別降低了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.
“越早發(fā)現乳腺癌，對病人越好，”谷歌健康中心英國分部負責人多米尼克•金告訴法新社。
"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."
“我們認為這項技術能夠支持并最終使專家或患者從他們得到的診斷中獲得最佳結果。”
研究人員稱，一種電腦程序可以通過常規(guī)掃描準確識別乳腺癌，而且它的準確率比人類專家的更高。他們希望該電腦程序可以在與乳腺癌這一全球殺手的斗爭中取得突破。
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癥之一，僅去年一年就有200多萬名新確診的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者沒有明顯癥狀的時候，定期篩查對于發(fā)現疾病的早期癥狀至關重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英國，50歲以上的婦女被建議每三年做一次乳房X光檢查，而其檢查結果由兩位單獨的專家進行分析。
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.
但對掃描結果的解讀也有可能出錯，而且在所有乳房X光檢查結果中，有一小部分要么是假陽性（將健康病人誤診為患有癌癥），要么是假陰性（在疾病的傳播過程中，沒有診斷出疾病）。
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員已訓練出一個人工智能模型，它可以通過乳房掃描來檢測英國和美國數千名女性是否罹患癌癥。
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.
實際上，醫(yī)生們已經檢查過這些圖像了，不過與臨床環(huán)境不同的是，這臺機器不知道病人的病史，也沒有據此來進行診斷。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
該研究團隊發(fā)現，他們的人工智能模型可以通過掃描檢查來預測乳腺癌，而且其準確度與放射科專家相當。
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，該人工智能模型還顯示，癌癥被錯誤識別的比例有所下降，其中美國降低了5.7%，英國降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain.
美國和英國的漏診率也分別降低了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.
“越早發(fā)現乳腺癌，對病人越好，”谷歌健康中心英國分部負責人多米尼克•金告訴法新社。
"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."
“我們認為這項技術能夠支持并最終使專家或患者從他們得到的診斷中獲得最佳結果。”
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.
研究人員稱，一種電腦程序可以通過常規(guī)掃描準確識別乳腺癌，而且它的準確率比人類專家的更高。他們希望該電腦程序可以在與乳腺癌這一全球殺手的斗爭中取得突破。
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癥之一，僅去年一年就有200多萬名新確診的病例。
Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.
在患者沒有明顯癥狀的時候，定期篩查對于發(fā)現疾病的早期癥狀至關重要。
In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analysed by two independent experts.
在英國，50歲以上的婦女被建議每三年做一次乳房X光檢查，而其檢查結果由兩位單獨的專家進行分析。
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.
但對掃描結果的解讀也有可能出錯，而且在所有乳房X光檢查結果中，有一小部分要么是假陽性（將健康病人誤診為患有癌癥），要么是假陰性（在疾病的傳播過程中，沒有診斷出疾?。?。
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員已訓練出一個人工智能模型，它可以通過乳房掃描來檢測英國和美國數千名女性是否罹患癌癥。
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.
實際上，醫(yī)生們已經檢查過這些圖像了，不過與臨床環(huán)境不同的是，這臺機器不知道病人的病史，也沒有據此來進行診斷。
The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.
該研究團隊發(fā)現，他們的人工智能模型可以通過掃描檢查來預測乳腺癌，而且其準確度與放射科專家相當。
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，該人工智能模型還顯示，癌癥被錯誤識別的比例有所下降，其中美國降低了5.7%，英國降低了1.2%。
It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain. 美國和英國的漏診率也分別降低了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.
“越早發(fā)現乳腺癌，對病人越好，”谷歌健康中心英國分部負責人多米尼克•金告訴法新社。
"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."
“我們認為這項技術能夠支持并最終使專家或患者從他們得到的診斷中獲得最佳結果。”
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