This course introduces you to a framework for successful and ethical medical data mining. We will explore the variety of clinical data collected during the delivery of healthcare. You will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. We will also explore issues of fairness and bias that may arise when we leverage healthcare data to make decisions about patient care.
Este curso forma parte de Programa especializado: AI in Healthcare
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ofrecido por
Programa especializado: AI in HealthcareUniversidad de StanfordAcerca de este Curso
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Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 2 de 5 en
Nivel principiante
Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
Qué aprenderás
How to apply a framework for medical data mining
Ethical use of data in healthcare decisions
How to make use of data that may be inaccurate in systematic ways
What makes a good research question and how to construct a data mining workflow answer it
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 2 de 5 en
Nivel principiante
Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad 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 - Qué aprenderás en este curso
1 hora para completar
Asking and answering questions via clinical data mining
1 hora para completar
12 videos (Total 19 minutos), 2 lecturas, 3 cuestionarios
2 horas para completar
Data available from Healthcare systems
2 horas para completar
16 videos (Total 32 minutos), 3 lecturas, 4 cuestionarios
1 hora para completar
Representing time, and timing of events, for clinical data mining
1 hora para completar
12 videos (Total 20 minutos), 2 lecturas, 3 cuestionarios
2 horas para completar
Creating analysis ready datasets from patient timelines
2 horas para completar
18 videos (Total 33 minutos), 2 lecturas, 3 cuestionarios
Reseñas
Principales reseñas sobre INTRODUCTION TO CLINICAL DATA
por OA14 de mar. de 2021
The course program is very intuitive and challenging. Overall, it is a very good course and I will recommend it to anyone interested in understanding clinical data, in particular for data scientists.
por YX4 de nov. de 2020
Very clear and well-organized course. I have learned quite a bit about the different types of clinical data, why they are important, and how to transfer them to analytical useable data sets.
por SR26 de oct. de 2020
Good introductory course covering key features of the various data that are gathered or used in health care. No prior knowledge about the topic is required.
por NJ19 de nov. de 2020
It would be helpful to be able to see all items that need to be completed. I took the final test and it says I've only completed 2 of 5 courses.
Acerca de Programa especializado: 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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Is this activity accredited for Continuing Medical Education (CME)?
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