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Early Prediction of Neonatal Jaundice using Artificial Intelligence Techniques

Yogesh Kumar, Nimisha Patel, Apeksha Koul, Anish Gupta

20222022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)21 citationsDOI

Abstract

Jaundice in newborns is a prevalent problem all over the world. This syndrome can induce brain damage and kernicterus, which is characterized by repeated and uncontrollable movements, an upward gaze, and hearing loss. As a result, early detection and treatment can prevent long-term harm. As a result, in this study, we have investigated several researchers' strategies for detecting jaundice among newborn babies using various artificial intelligence-based techniques. We have also drawn some findings based on our analysis of the multiple AI techniques. In addition, the report highlighted their accomplishments and the challenges they have faced in this field.

Topics & Concepts

KernicterusJaundiceHarmComputer scienceArtificial intelligencePediatricsMedicinePsychologySurgerySocial psychologyNeonatal Health and BiochemistryNeonatal and fetal brain pathologyNeonatal Respiratory Health Research
Early Prediction of Neonatal Jaundice using Artificial Intelligence Techniques | Litcius