Computer-aided diagnosis of hepatocellular carcinoma fusing imaging and structured health data.
Alan Baronio MenegottoCarla Diniz Lopes BeckerSílvio César CazellaPublished in: Health information science and systems (2021)
The classification performance achieved with the multimodal deep learning algorithm is higher than human specialists diagnostic performance using only CT for diagnosis. Even though the results are promising, the multimodal deep learning architecture used for hepatocellular carcinoma prediction needs more training and test processes using different datasets before the use of the proposed algorithm by physicians in real healthcare routines. The additional training aims to confirm the classification performance achieved and enhance the model's robustness.
Keyphrases
- deep learning
- healthcare
- artificial intelligence
- machine learning
- convolutional neural network
- endothelial cells
- pain management
- primary care
- big data
- virtual reality
- high resolution
- public health
- computed tomography
- mental health
- health information
- electronic health record
- rna seq
- mass spectrometry
- magnetic resonance imaging
- induced pluripotent stem cells
- risk assessment
- positron emission tomography
- photodynamic therapy
- human health
- climate change
- fluorescence imaging