Closing Keynote
summary
Presents evidence that an alternating pattern of “léthargie paroxystique” and “agitation paroxystique” in fetal heart-rate/behavior signals can indicate fetal hypoxia earlier than classic low variability. Uses entropy measures and very-short-term variability analysis plus an automated classifier (developed with a mathematician) to label behavioral states and flag suspicious epochs; a prototype algorithm exists, while real-time clinical alarms and broad validation are still pending.
AI-written summary · about
chapters (10)
- 0:00Closing keynote
- 0:45Keynote speaker
- 1:50Medicine to computing
- 3:36Prenatal monitoring
- 7:11Fetal oxygen deficiency
- 10:03Paroxysmal rhythms
- 12:31Medicine meets computing
- 14:39Math collaboration
- 15:43Results and outlook
- 16:36Q&A
related talks
05mMaking Sense of Sleep: Multimodal Sleep Stage Classification in a Large, Diverse Population ...
19mInTheMoodForLife: Analyzing Sleep to Better Manage Mood Disorders
42mMachine learning with ventilator data
31mBig data for tiny patients: Applying ML to pediatrics
28mHow Smart is the ECG? Lessons from Advanced ECG Analytics
06mHeartQuake: Accurate Low-Cost Non-Invasive ECG Monitoring Using Bed-Mounted Geophones
20mEmpowering Education and Therapy with Data Science
01h 13mHealth Monitoring with Wireless Sensors and Machine Learning
