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  • The quest for artificial intelligence began more than 80 years ago.

    人工知能 (AI) の探求は、80 年以上前に始まりました。

  • The idea was that computer technology would one day be powerful enough to carry out tasks better and more efficiently than humans.

    AI とは、いつの日かコンピュータ技術が強大になり、人間よりも上手く効率的にタスクをこなせるようになる、という考えでした。

  • We've got to actually say hello to it.


  • Today AI has come of age.

    今日、AI は十分に発達しています。

  • It's already having an impact on many parts of human life, from self-driving cars to finding soul mates.

    自動運転機能付の車から、運命の相手を見つけることに至るまで、AI は既に、人間生活の多くの部分に影響をもたらしています。

  • But perhaps its greatest impact will be on medicine and the way we monitor human health.

    でもおそらく、医学や、人間の健康を監視する方法こそ、AI の力が最も及んでいる分野でしょう。

  • Dr. Eric Topol is one of the most influential doctors in digital medicine.

    エリック・トポル医師は、デジタル医学界における最大の権威の 1 人です。

  • The pioneering American cardiologist has helped develop drugs that have saved countless lives.


  • He's now at the forefront of the AI revolution in health care.

    彼は現在、ヘルスケア分野における AI 革命の最前線に立っています。

  • These are his prescriptions for transforming the future of human health.


  • The overarching goal is to bring back the humanity.


  • If we do this right we can rescue the problems of healthcare.


  • How AI will transform the future of health care.

    AI は、ヘルスケアの将来をいかに変えるのか。

  • The doctor-patient relationship is a founding principle of health care and medicine.


  • The first step is to eliminate keyboards and computer screens and clinical encounters.


  • 1. Use AI for doctors' clinical paperwork.

    1. 臨床に関連する文書業務に AI を活用する

  • Some doctors in the West can spend up to twice as many hours on medical paperwork than with their patients.

    西洋世界における医者は、患者対応の 2 倍の時間を、医療文書業務に割くこともある、と言われています。

  • In the years ahead we should be able to eliminate the data clerk functions of clinicians.


  • These are mutually hated as much by patients as by doctors and clinicians.


  • AI tools such as speech recognition technology, but in our common place in homes, could be used in clinical settings for capturing data and notes, allowing doctors to concentrate on people.

    音声認識技術などの AI ツールは現在、家庭によく普及しています。これらをデータやメモの記録用に臨床面で活用すれば、医者は患者に集中できます。

  • 2. Use machines to reduce errors.

    2. 機械を活用し、間違いを削減する

  • We have a problem with accuracy and efficiency.


  • Trained on a huge resource of medical data, the power of AI learning can read some images more accurately than humans.

    AI は膨大な医療データに照準を合わせているため、その学習能力を活用すれば、人間より正確に画像を読み取ることが可能です。

  • Whether it's a pattern like a scan, or a slide, or prediction.


  • AI can really rev up the accuracy and that is important for a better diagnosis, better treatments, better outcomes, lower-cost.

    AI を使えば正確性を向上させられます。これはより良い診断、治療、結果をもたらし、コストを下げることにおいて重要です。

  • Powerful Machines can interpret scans 150 times faster than radiologists and can work 24 hours a day.

    強力な機械であれば、放射線科医の 150 倍の速さでスキャンを解釈でき、24 時間働くことができます。

  • AI can even suggest a diagnosis.

    AI は、診断を提案することもできます。

  • Many conditions could be AI-diagnosed and so the time that a doctor comes into play is very specific to important diagnosis.

    多くの症状は AI で診断を下すことができるため、実際に医者が携わるのは、重要な診断のみに限られます。

  • 3. Harvesting data to improve outcomes.

    3. 成果の改善のためにデータを収集する

  • Data is critical for improving our understanding of disease and illness.


  • The more we understand, the better the chances of preventing diagnosing and curing.


  • But currently, only about 5% of medical data is used effectively.

    しかし現在、効率的に活用されている医療データは、たった 5 %ほどです。

  • We had a problem with generating so much data, terabytes of data for each person, but we didn't have a way to analyze.

    患者 1 人につき何テラバイトという、大量のデータを生み出す問題がありました。しかしそれを分析する方法がなかったのです。

  • We didn't have a way to extract the juice, the distillate of this.


  • Now we do, and that's what artificial intelligence is really about.

    でも今なら、その方法があります。それこそ、AI の本質なのです。

  • Harness to wireless devices, AI could oversee every facet of people's health data from family history to food intake, to exercise.

    ワイヤレス機器を活用すれば、家系から摂食、運動に至るまで、AI で人のあらゆる健康データを管理できます。

  • People will have the opportunity to have this real integrated view of themselves to help prevent illness, to help guide them for better management of conditions.


  • Over time, we'll see this virtual coach for promoting health.


  • Constant AI monitoring could transform the most prolific diseases that demand the most care, such as diabetes.

    AI を常時監視しておくことで、糖尿病など手厚いケアを要する、患者の多い病のあり方を、変えることができるでしょう。

  • This would empower people to take charge of their own health.


  • 4. Treat patient at home, not in hospital.

    4. 病院でなく家庭で患者を治療する

  • Another way that AI will kick in over time is to get rid of hospital rooms.

    今後、AI が果たすであろう別の役目は、病室の削減です。

  • We can monitor patients in the comfort of their own home because they can have the sensors that would provide the same type of monitoring as if someone was in the intensive care unit.

    自宅の落ち着いた環境で、患者を監視できるようになるのです。ICU で受けるような監視と同様のセンサーを、自宅に設置できるからです。

  • Caring for people outside of medical settings would not only prevent hospital-acquired disease, it could also save money.


  • All these things favor this shift of reliance on a patient's bedroom rather than the hospital room.


  • We're talking about a whole lot of people that don't need to be employed in the hospital setting.


  • That is a great way to reduce the burden in the future.


  • In the United States, a hospital costs five thousand dollars a night, so you could get a lot of data plans that go for years for that cost.

    アメリカでは、一晩入院すると 5000 ドルかかります。それだけ払えば、何年分ものデータプランが買えますよね。

  • If the clinical community stands up for patients and say all the power, efficiency, productivity, workflow from AI is going to be used to give the gift of time to doctors and nurses and patients, that's where we flip this thing and achieve a rescue mission for health.

    臨床分野が患者のために一丸となり、AI から得られる全てのパワー、効率性、生産性、ワークフローを、「 時間 」という形で医者や看護師、患者に与えられるのなら、私たちはこの問題に立ち向かい、健康を取り戻す使命を果たすのです。

The quest for artificial intelligence began more than 80 years ago.

人工知能 (AI) の探求は、80 年以上前に始まりました。

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