Lead Guest Editor
Prof. Elena Bonanno
Guest Editors
Orazio Schillaci, University of Rome Tor Vergata, Rome, Italy
Manuel Scimeca, San Raffaele University, Rome, Italy
Nicola Toschi, Massachusett
s General Hospital and Harvard Medical School, Boston, USA
Carlo Catapano, Università della Svizzera Italiana (USI), Bellinzona, Switzerland
https://www.hindawi.com/journals/cmmi/si/819152/cfp/
Call for paper
Personalized medicine is one of the main objectives of both basic and translational research within the larger paradigm of the so-called P4 medicine (Predictive, Preventive, Personalized, and Participatory). In order to achieve this goal and specifically to tailor therapeutic interventions to interindividual variability and the unique pathophysiological profiles of individual patients, synergistic and transdisciplinary data integration modelling and interpretation are indispensable. In the last three years, unique breakthroughs in the field of artificial intelligence (and deep learning in particular) have unlocked access to unprecedented data integration and prediction capabilities, allowing the seamless combination of information from, e.g., nuclear medicine, radiology, and anatomic pathology. On the data side, biomedical imaging in general and molecular imaging in particular can provide a foundation for the quantitative study of underlying mechanisms involved in human diseases and thus identify new promising molecular targets for both diagnosis and therapy. Therefore, the construction of a structured transdisciplinary collaboration and mutual enhancement model, both at a clinical and basic research level, can greatly accelerate the quest towards real, implementable personalized medicine strategies.
The focus of this special issue will be research dealing with potential new molecular targets for human disease therapy through the application of medical imaging techniques (e.g., radiological, molecular imaging, histopathology) and their integration using artificial intelligence. In particular, the special issue will be focused on in vitro, preclinical, and clinical investigations reporting findings aiming to advance the field of personalized medicine. Review articles focused on these topics are also welcome.
Potential topics include but are not limited to the following:
Management of patients in the digital era: from basic science to personalized medicine
Identification of new early prognostic/predictive biomarkers of oncological diseases
New approaches for diagnosis and treatment of neurological disorders
Emerging protocols for imaging of chronic inflammatory diseases
Biomedical imaging data integration through artificial intelligence approaches
Imaging mouse models of human diseases
Deep learning for joint multiscale biomedical image analysis (e.g., from digital pathology to brain and body imaging)
Artificial intelligence techniques for assisted diagnosis and prediction of longitudinal disease progression
Analysis of clinical appropriateness through machine learning
Prediction of clinical, neurophysiological, or molecular outcome measures through deep learning approaches
Deep learning in nuclear medicine and molecular imaging
Radiomics and deep learning in medical imaging
Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/cmmi/nfmi/.
Submission Deadline Friday, 29 March 2019
Publication Date August 2019
Papers are published upon acceptance, regardless of the Special Issue publication date. ... [more]