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Learning the impact of acute and chronic diseases on forecasting neonatal encephalopathy

  • Published:2021-11 Issue: Volume:211 Page:106397
  • ISSN:0169-2607
  • Container-title:Computer Methods and Programs in Biomedicine
  • language:en
  • Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Jeong EugeneORCID,Osmundson Sarah,Gao Cheng,Edwards Digna R. Velez,Malin Bradley,Chen YouORCID

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference43 articles.

1. Executive summary: neonatal encephalopathy and neurologic outcome, second edition. report of the American College of Obstetricians and Gynecologists’ task force on neonatal encephalopathy;Obstet. Gynecol.,2014

2. Long-term outcome after neonatal hypoxic-ischaemic encephalopathy;de Vries;Arch. Dis. Child. Fetal Neonatal Ed.,2010

3. Neuropsychological and educational problems at school age associated with neonatal encephalopathy;Marlow;Arch. Dis. Child. Fetal Neonatal Ed.,2005

4. No cry at birth: global estimates of intrapartum stillbirths and intrapartum-related neonatal deaths;Lawn;Bull. World Health Organ.,2005

5. Lifetime costs of cerebral palsy;Kruse;Dev. Med. Child Neurol.,2009

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1. Clinical Insight: Comparative Analysis of Deep Learning Models for Disease Prediction across Multifaceted Datasets;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26

2. Machine Learning-Based Approach for Early Detection and Prediction of Chronic Diseases;2023 1st DMIHER International Conference on Artificial Intelligence in Education and Industry 4.0 (IDICAIEI);2023-11-27

3. Identification and Prediction of Chronic Diseases Using Machine Learning Approach;Journal of Healthcare Engineering;2022-02-25
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