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Clinician AI Use; Predicting Bad Infant Outcomes in Labor; Donor Heart Distribution

(MedPage Today) -- TTHealthWatch is a weekly podcast from Texas Tech. In it, Elizabeth Tracey, director of electronic media for Johns Hopkins Medicine in Baltimore, and Rick Lange, MD, president of Texas Tech Health El Paso, look at the top medical...

Clinician AI Use; Predicting Bad Infant Outcomes in Labor; Donor Heart Distribution

In a recent study published in The Lancet, researchers have developed a new prognostic model to predict the risk of severe fetal compromise at birth during labor. This innovative model combines clinical risk factors with the first 20 minutes of fetal monitoring, known as cardiotocography (CTG). The study included data from singleton births at 36 weeks or more of gestation who underwent CTG monitoring, both spontaneous and induced labor.

The researchers developed the model using a large database, then trained and tested it on another dataset, and externally validated it on a third dataset. The model incorporated factors such as maternal age, gestational age, nulliparity, preeclampsia, diabetes during pregnancy, and the presence of thick meconium in the amniotic fluid.

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She made aliyah at 16 - today, she's teaching the next generation about AI

Since July 2024, Prof. Claudia V. Goldman has been an associate professor in the Data Science Department at the Hebrew University Business School in Jerusalem.

  • Prof. Claudia V. Goldman made aliyah from Buenos Aires at 16
  • Holds BSc, MSc, PhD in Computer Science from Hebrew University
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