Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization.

ABSTRACT: In the past decade, there has been a sharp increase in publications describing applications of convolutional neural networks (CNNs) in medical image analysis. However, recent reviews have warned of the lack of reproducibility of most such studies, which has impeded closer examination of the models and, in turn, their implementation in healthcare. On the other hand, the performance of these models is highly dependent on decisions on architecture and image pre-processing. In this work, we assess the reproducibility of three studies that use CNNs for head and neck cancer outcome prediction by attempting to reproduce the published results. In addition, we propose a new network structure and assess the impact of image pre-processing and model selection criteria on performance. We used two publi

SUBMITTER: Mateus P 

PROVIDER: S-EPMC10598263 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature