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  • [SLOW BREATHING]

  • [BIRDS CHIRPING]

  • [BREATHING]

  • [RAIN]

  • LEWIS WANJOHI: Sound analysis is used in so many fields--

  • [HORNS]

  • [PLAYING TROMBONES]

  • --such as identification of music--

  • [MUSIC PLAYING]

  • --and the identification of the type of animal--

  • [MEOW]

  • --based on the sounds that they produce.

  • Sound is critical to what we are doing

  • because physiological sounds are very important in medicine.

  • But the traditional stethoscope hasn't

  • changed for close to 200 years.

  • The doctor is limited by the human ear.

  • And they cannot hear specific frequencies.

  • This method is very inaccurate and causes

  • a lot of misdiagnoses.

  • Our mission is to use machine learning and TensorFlow

  • to revolutionize the diagnosis and treatment

  • of respiratory diseases in low resource areas

  • such as sub-Saharan Africa.

  • The Tambua app is a powerful screening tool

  • that helps doctors make decisions quickly.

  • The core technology is trying to mimic the human auditory

  • system.

  • Once the patient walks in, the doctor

  • collects the lung sounds with symptoms, risk factors,

  • and vitals of the patient, and then the Tambua app

  • combines all that information and gives the doctor

  • a probability of the patient having a specific respiratory

  • disease.

  • SULEIMAN NDORO: [NON-ENGLISH] breathe sounds?

  • SPEAKER: Yeah.

  • LEWIS WANJOHI: Eric introduced TensorFlow to us

  • because he felt that we can use TensorFlow

  • to go through all the stages of development

  • to deployment of our model.

  • ERIC KIRIMA: Our model uses spectograms.

  • We take sound data from the digital stethoscope

  • and convert it into a visual problem

  • that the computer can best identify.

  • We have worked with a number of clinics and pathologists.

  • And we are able to collect data from 621 patients.

  • And then we use that data now to build our machine learning

  • model.

  • LEWIS WANJOHI: Once we had trained and evaluated

  • our machine learning model, we deployed it on our Tambua app.

  • TensorFlow Lite helps us to perform

  • an inference on our mobile device

  • without the need of a connection,

  • so doctors can use the Tambua app offline

  • without connecting to the cloud.

  • There are 216 health care facilities

  • that are using the Tambua app and the Tambua devices.

  • These clinics are spread out, and some

  • are very rural clinics.

  • SULEIMAN NDORO: It's certainly a nice project, I think.

  • I can use it [INAUDIBLE] plus devoid of sounds.

  • Then when I add the clinical history

  • and other physical examination, there's

  • no need for me to take this patient for an X-ray.

  • Misdiagnosis, which is one of the problems leading

  • to deaths in Kenya, is really creating a menace.

  • Tambua is helping me.

  • It shows me even the things that I would have missed in case

  • I had the traditional way of doing it.

  • LEWIS WANJOHI: Over 2.5 million people

  • die each year because of pneumonia, asthma, COPD,

  • and pulmonary tuberculosis.

  • I believe that we can use machine

  • learning in treatment and management

  • of these respiratory diseases.

[SLOW BREATHING]

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B1 中級

Powered by TensorFlow: 機械学習を利用して医師が呼吸器疾患を検出するのに役立つ (Powered by TensorFlow: Helping doctors detect respiratory diseases using machine learning)

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    林宜悉 に公開 2021 年 01 月 14 日
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