About 10% to 15% of patients with ischemic stroke have a history of cancer, half of whom have active malignancy at the time of stroke. With improved cancer treatments extending patient survival, the ...
Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
Abstract: Alzheimer’s Disease (AD) and Dementia represent critical healthcare challenges worldwide, underscoring the need for reliable and early diagnostic tools. This study presents an innovative ...
Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
ABSTRACT: High-quality data is essential for hospitals, public health agencies, and governments to improve services, train AI models, and boost efficiency. However, real data comes with challenges: ...
ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, particularly for planning treatment strategies in patients with maxillary transverse deficiency (MTD). Although ...
当時はRNNやLSTMと呼ばれるモデル構造が主流であり、 Transformer と呼ばれるモデル構造をベースにしたBERTは、かなり目新しいものでした。 また、PyTorchなど深層学習用のライブラリもまだまだ発展途上であり、近年までBERTを取り巻く環境は混沌としていました。
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