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Predicting Visit Cost of Obstructive Sleep Apnea Using Electronic Healthcare Records With Transformer.

Zhaoyang ChenLina Siltala-LiMikko LassilaPekka MaloEeva VilkkumaaTarja SaaresrantaArho Veli Virkki
Published in: IEEE journal of translational engineering in health and medicine (2023)
The proposed method makes prediction with the most of the available high-quality data by carefully exploiting details, which are not directly relevant for answering the question of the next year's likely expenditure. Clinical and Translational Impact Statement: Public Health- Lack of high-quality source data hinders data-driven analytics-based research in healthcare. The paper presents a method that couples data augmentation and prediction in cases of scant healthcare data.
Keyphrases
  • healthcare
  • big data
  • electronic health record
  • public health
  • obstructive sleep apnea
  • machine learning