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A fully deep learning model for the automatic identification of cephalometric landmarks

Kim YH, Lee C, Ha EG, Choi YJ, Han SS

Purpose This study aimed to propose a fully automatic landmark identification model based on a deep learning algorithm using real clinical data and to verify its accuracy considering inter-examiner variability. Materials and...
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: A systematic review

Musri N, Christie B, Arief Ichwan SJ, Cahyanto A

Purpose The aim of this study was to analyse and review deep learning convolutional neural networks for detecting and diagnosing early-stage dental caries on periapical radiographs. Materials and Methods In order to conduct...
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Prediction of Hospital Charges for the Cancer Patients with Data Mining Techniques

Kang JO, Chung SH, Suh YM

  • KMID: 2357289
  • J Korean Soc Med Inform.
  • 2009 Mar;15(1):13-23.
OBJECTIVE: Predictions of hospital charges for cancer patients are very important, because they provide a basis for allocating medical resources in the hospital and for establishing national medical policies. But...
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