A Combined Radiomics and Machine Learning Approach to Overcome the Clinicoradiologic Paradox in Multiple Sclerosis.
Giuseppe PontilloSilvia TommasinRenato CuocoloMaria PetraccaNikolaos PetsasLorenzo UggaAntonio CarotenutoCarlo PozzilliRosa IodiceRoberta LanzilloMario QuarantelliVincenzo Brescia MorraEnrico TedeschiPatrizia PantanoSirio CocozzaPublished in: AJNR. American journal of neuroradiology (2021)
The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.
Keyphrases
- multiple sclerosis
- machine learning
- white matter
- big data
- contrast enhanced
- deep learning
- high resolution
- electronic health record
- resting state
- artificial intelligence
- convolutional neural network
- magnetic resonance
- optical coherence tomography
- squamous cell carcinoma
- cerebral ischemia
- functional connectivity
- computed tomography
- mass spectrometry
- blood brain barrier