Artwork

محتوای ارائه شده توسط Uppsala Monitoring Centre. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Uppsala Monitoring Centre یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
Player FM - برنامه پادکست
با برنامه Player FM !

Uppsala Reports Long Reads – Weeding out duplicates to better detect side effects

25:02
 
اشتراک گذاری
 

Manage episode 436241633 series 2749727
محتوای ارائه شده توسط Uppsala Monitoring Centre. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Uppsala Monitoring Centre یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Duplicate reports are a big problem when it comes to signal detection, but with the help of machine learning and new ways of comparing reports, we may more effectively detect them.

This episode is part of the Uppsala Reports Long Reads series – the most topical stories from UMC’s pharmacovigilance news site, brought to you in audio format. Find the original article here.

After the read, we speak to author Jim Barrett, Senior Data Scientist at UMC, to learn more about the duplicate detection algorithm and UMC’s work to develop AI resources for pharmacovigilance.
Tune in to find out:

  • How the new algorithm handles duplicates in VigiBase
  • About different approaches for developing algorithms
  • Why it can be challenging to evaluate the performance of an algorithm

Want to know more?

Finally, don’t forget to ­subscribe to the monthly Uppsala Reports newsletter for free regular updates from the world of pharmacovigilance.

Join the conversation on social media
Follow us on X, LinkedIn, or Facebook and share your thoughts about the show with the hashtag #DrugSafetyMatters.
Got a story to share?
We’re always looking for new content and interesting people to interview. If you have a great idea for a show, get in touch!
About UMC
Read more about Uppsala Monitoring Centre and how we work to advance medicines safety.

  continue reading

فصل ها

1. Uppsala Reports Long Reads – Weeding out duplicates to better detect side effects (00:00:00)

2. Intro (00:00:09)

3. Article read (00:01:12)

4. Welcome, Jim! (00:05:57)

5. Definitions of AI, machine learning and algorithms (00:07:19)

6. How do we develop algorithms at UMC? (00:08:47)

7. Evaluating the performance of algorithms (00:10:13)

8. How many algorithms has UMC developed? (00:13:09)

9. How many duplicates in VigiBase? (00:13:45)

10. Which duplicate to keep, and which to weed out? (00:15:29)

11. Other examples of algorithms used in pharmacovigilance (00:18:10)

12. Where will we be in a couple of years? (00:20:18)

13. Pitfalls to be mindful of, heading into the future (00:21:47)

14. A dream algorithm? (00:22:32)

15. Thank you and goodbye (00:23:56)

16. Outro (00:24:09)

49 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 436241633 series 2749727
محتوای ارائه شده توسط Uppsala Monitoring Centre. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Uppsala Monitoring Centre یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Duplicate reports are a big problem when it comes to signal detection, but with the help of machine learning and new ways of comparing reports, we may more effectively detect them.

This episode is part of the Uppsala Reports Long Reads series – the most topical stories from UMC’s pharmacovigilance news site, brought to you in audio format. Find the original article here.

After the read, we speak to author Jim Barrett, Senior Data Scientist at UMC, to learn more about the duplicate detection algorithm and UMC’s work to develop AI resources for pharmacovigilance.
Tune in to find out:

  • How the new algorithm handles duplicates in VigiBase
  • About different approaches for developing algorithms
  • Why it can be challenging to evaluate the performance of an algorithm

Want to know more?

Finally, don’t forget to ­subscribe to the monthly Uppsala Reports newsletter for free regular updates from the world of pharmacovigilance.

Join the conversation on social media
Follow us on X, LinkedIn, or Facebook and share your thoughts about the show with the hashtag #DrugSafetyMatters.
Got a story to share?
We’re always looking for new content and interesting people to interview. If you have a great idea for a show, get in touch!
About UMC
Read more about Uppsala Monitoring Centre and how we work to advance medicines safety.

  continue reading

فصل ها

1. Uppsala Reports Long Reads – Weeding out duplicates to better detect side effects (00:00:00)

2. Intro (00:00:09)

3. Article read (00:01:12)

4. Welcome, Jim! (00:05:57)

5. Definitions of AI, machine learning and algorithms (00:07:19)

6. How do we develop algorithms at UMC? (00:08:47)

7. Evaluating the performance of algorithms (00:10:13)

8. How many algorithms has UMC developed? (00:13:09)

9. How many duplicates in VigiBase? (00:13:45)

10. Which duplicate to keep, and which to weed out? (00:15:29)

11. Other examples of algorithms used in pharmacovigilance (00:18:10)

12. Where will we be in a couple of years? (00:20:18)

13. Pitfalls to be mindful of, heading into the future (00:21:47)

14. A dream algorithm? (00:22:32)

15. Thank you and goodbye (00:23:56)

16. Outro (00:24:09)

49 قسمت

همه قسمت ها

×
 
Loading …

به Player FM خوش آمدید!

Player FM در سراسر وب را برای یافتن پادکست های با کیفیت اسکن می کند تا همین الان لذت ببرید. این بهترین برنامه ی پادکست است که در اندروید، آیفون و وب کار می کند. ثبت نام کنید تا اشتراک های شما در بین دستگاه های مختلف همگام سازی شود.

 

راهنمای مرجع سریع