Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles.
Este curso faz parte do Programa de cursos integrados AI in Healthcare
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Programa de cursos integrados AI in HealthcareUniversidade de StanfordInformações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 3 de 5 no
Nível iniciante
Aprox. 12 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
O que você vai aprender
Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.
Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.
Learn important approaches for leveraging data to train, validate, and test machine learning models.
Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 3 de 5 no
Nível iniciante
Aprox. 12 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade de Stanford
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Programa - O que você aprenderá com este curso
2 horas para concluir
Why machine learning in healthcare?
2 horas para concluir
7 vídeos (Total 34 mín.), 6 leituras, 3 testes
2 horas para concluir
Concepts and Principles of machine learning in healthcare part 1
2 horas para concluir
8 vídeos (Total 51 mín.), 2 leituras, 3 testes
2 horas para concluir
Concepts and Principles of machine learning in healthcare part 2
2 horas para concluir
10 vídeos (Total 63 mín.), 3 leituras, 3 testes
2 horas para concluir
Evaluation and Metrics for machine learning in healthcare
2 horas para concluir
5 vídeos (Total 35 mín.), 2 leituras, 3 testes
Avaliações
Principais avaliações do FUNDAMENTALS OF MACHINE LEARNING FOR HEALTHCARE
por MN2 de Jan de 2021
Good course but the language needs to be simpler. Sometimes simple facts are complicated with the use of high pedigree words that don't really add much to conveying the overall message.
por AJ8 de Set de 2020
Amazing course teaching the innumerous opportunities in the healthcare sector and the application of AI in the same. Beautifully drafted course with intriguing tutorials and exercises.
por LA1 de Abr de 2021
This was a great course, the presenters really gave a clear view about the differences which could happen when working with health related data set. Very well done,
por LS26 de Set de 2020
Interesting and well crafted, it is mostly at an introductory level, but accurate and with many details regarding how to apply ML to healthcare. Worth to follow.
Sobre Programa de cursos integrados AI in Healthcare
Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system -- such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.
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