Este curso forma parte de Programa especializado: AI in Healthcare

4.5
estrellas
134 calificaciones

Tina Hernandez-Boussard +1 instructores más

6866 ya inscrito

ofrecido por

Programa especializado: AI in HealthcareUniversidad de Stanford

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With artificial intelligence applications proliferating throughout the healthcare system, stakeholders are faced with both opportunities and challenges of these evolving technologies. This course explores the principles of AI deployment in healthcare and the framework used to evaluate downstream effects of AI healthcare solutions.
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.  Visit the FAQs below for important information regarding 1) Date of original release and Termination or expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.

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Curso 4 de 5 en

Programa especializado: AI in Healthcare

Nivel principiante

Aprox. 11 horas para completar

Inglés (English)

Qué aprenderás

Principles and practical considerations for integrating AI into clinical workflows
Best practices of AI applications to promote fair and equitable healthcare solutions
Challenges of regulation of AI applications and which components of a model can be regulated
What standard evaluation metrics do and do not provide

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 4 de 5 en

Programa especializado: AI in Healthcare

Nivel principiante

Aprox. 11 horas para completar

Inglés (English)

Instructores

Calificación del instructor

4,46/5 (51 calificaciones)

Tina Hernandez-Boussard

Associate Professor

Medicine (Biomedical Informatics), of Biomedical Data Science and of Surgery

8235 alumnos

2 cursos

Mildred Cho

Professor

Department of Pediatrics Division of Medical Genetics

26.982 alumnos

2 cursos

ofrecido por

Universidad de Stanford

Programa - Qué aprenderás en este curso

Semana

Semana 1

1 hora para completar

AI in Healthcare

1 hora para completar

10 videos (Total 30 minutos), 2 lecturas, 3 cuestionarios

Semana

Semana 2

2 horas para completar

Evaluations of AI in Healthcare

2 horas para completar

15 videos (Total 41 minutos), 2 lecturas, 4 cuestionarios

15 videos

Learning Objectives1m

Recap: Framework1m

Stakeholders1m

Clinical Utility1m

Outcome: Action Pairing, An Overview4m

Lead Time1m

Type of Action3m

OAP Examples3m

Number Needed to Treat2m

Net Benefits2m

Decision Curves4m

Feasibility overview4m

Implementation Costs1m

Clinical Evaluation and Uptake4m

Summary1m

2 lecturas

Study Guide Module 25m

Citations and Additional Readings

4 ejercicios de práctica

Reflection Exercise 110m

Reflection Exercise 210m

Reflection Exercise 310m

Knowledge Check30m

Semana

Semana 3

2 horas para completar

AI Deployment

2 horas para completar

19 videos (Total 47 minutos), 2 lecturas, 5 cuestionarios

19 videos

Learning Objectives1m

The Problem1m

Practical Questions Prior to Deployment3m

Deployment Pathway1m

Design and Development3m

Stakeholder Involvement2m

Data Type and Sources3m

Settings3m

In Silico Evaluation2m

Net Utility & Work Capacity2m

Statistical Validity1m

Care Integration, Silent Mode2m

Clinical Integration, Considerations2m

Technical Integration1m

Deployment Modalities2m

Continuous Monitoring and Maintenance2m

Challenges of Deployment5m

Sepsis Example1m

Summary1m

2 lecturas

Study Guide Module 35m

Citations and Additional Readings

5 ejercicios de práctica

Reflection Exercise 110m

Reflection Exercise 210m

Reflection Exercise 310m

Reflection Exercise 410m

Knowledge Check30m

Semana

Semana 4

2 horas para completar

Downstream Evaluations of AI in Healthcare: Bias and Fairness

2 horas para completar

18 videos (Total 41 minutos), 2 lecturas, 5 cuestionarios

18 videos

Learning Objectives2m

Real World Examples of AI Bias4m

Introduction - Types of Bias41s

Historical Bias2m

Representation Bias1m

Measurement Bias1m

Aggregation Bias2m

Evaluation Bias1m

Deployment Bias1m

What is algorithmic Fairness2m

Anti-classification2m

Parity Classification1m

Calibration2m

Applying Fairness Measures2m

Lack of Transparency2m

Minimal Reporting Standards3m

Opportunities and Challenges2m

Summary2m

2 lecturas

Study Guide Module 45m

Citations and Additional Readings

5 ejercicios de práctica

Reflection Exercise 110m

Reflection Exercise 210m

Reflection Exercise 310m

Reflection Exercise 410m

Knowledge Check30m

Reseñas

4.5

34 reseña

5 stars
69,40 %
4 stars
18,65 %
3 stars
6,71 %
2 stars
2,98 %
1 star
2,23 %

Principales reseñas sobre EVALUATIONS OF AI APPLICATIONS IN HEALTHCARE

por BA27 de dic. de 2020

Outstanding informational content and operating platform!

por GG12 de dic. de 2020

Thanks a lot for this great course, extremely practical, allowing to create a clear action plan for AI evaluation.

por JW7 de abr. de 2022

This course was really valuable for linking and embedding my knowledge gained by reading FDA guidance documents and knowledge sharing from my Quality Assurance and Regulatory Affairs colleagues

por PJ9 de jul. de 2022

Useful content, but there is a lot of repetition early in the course.

Ver todas las reseñas

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.

In this specialization, we'll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically. This specialization is designed for both healthcare providers and computer science professionals, offering insights to facilitate collaboration between the disciplines. CME Accreditation The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. View the full CME accreditation information on the individual course FAQ page.

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.
Is this activity accredited for Continuing Medical Education (CME)?
Dates and Duration
Original Release Date: 08/10/2020
Expiration Date: 08/10/2023
Estimated Time to Complete: 9 hours and 30 minutes
CME Credits Offered: 9.50
Accreditation
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The Stanford University School of Medicine designates this enduring material for a maximum of 9.50 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Disclosures
The Stanford University School of Medicine adheres to ACCME Criteria, Standards and Policies regarding industry support of continuing medical education. There are no relevant financial relationships with ACCME-defined commercial interests for anyone who was in control of the content of this activity.

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Evaluations of AI Applications in Healthcare

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Qué aprenderás