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