Roberto Gerent, Gerente de Novos Negócios - Huawei Saiba mais em https://eventos.ecommercebrasil.com.br/congresso-ecommerce-saude-farma/

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HUAWEI CLOUD
AI-assisted CT patient screening for COVID-19
Hospital das Clinicas – USP
Abril/2020
Roberto Gerent

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COVID-19, a potential “once-in-a-century pathogen”
• Person-to-person spreading
• Infected within minutes
• Affects the entire population
• High Fatality Rate, more than 5%
• No specific medicine, no vaccine
• Irreversible sequelae
• 1~24 days of incubation period
• 50% of patients are asymptomatic
• Contagious
SOURCE: Google
Out-of-Control Spreading High Risk Long incubation period

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COVID-19 infection population grows rapidly and overwhelms the healthcare system
• Slow manual diagnosis cannot cope
with the rapid increase of patients
• Patients gathering causes cross-
infection
• Increased workload for radiologists
• Work fatigue and working overtime
leads to high misdiagnosis
• Multiple times of CT scan are
performed during the treatment
• Quantitative analysis is important for
forecast disease progression
Rapid increase of patients Huge Pressure on doctors Less indicator for follow-up

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Chest CT is a primary tool for COVID-19 detection
• Fast
• Easy to perform
• High sensitivity，98%
• High false negative rate
• Lack sensitivity during the first five
days of the disease，60-70%
Chest CT RT-PCR tests
The mean lead time in diagnosis of viral infection yielded by CT compared with laboratory results was 3 days
VS

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AI-Assisted Medical Image Diagnosis: A Faster and More Accurate Way to Diagnose COVID-19
Manual analysis: at least 12 minutes
Medical image
examination
equipment
AI + Doctor confirmation: 2 minutes Intelligent report
Traditional report
About 2 minutes
CT image + Radiologist
CT image + Huawei AI + Radiologist
CT examination Screening and diagnosis Reports
Traditional
AI-assisted
CT medical
image
PACS

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Inovação em Medicina
Diagnóstica
Hospital das Clínicas da Faculdade
de Medicina da Universidade de
São Paulo (Inrad-HCFMUSP)
Prêmio Abril & Dasa de Inovação
Médica reconhece trabalhos
desenvolvidos no Brasil para o
combate à COVID-19

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https://pubs.rsna.org/doi/10.1148/radiol.2020204267

12. Thank you.
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roberto.gerent@huawei.com