Rare diseases have a median diagnostic delay of two years. Because of their low individual frequency, an initial diagnosis based on phenotypic symptoms is not always easy, as practitioners might never have been exposed to patients suffering from the relevant disease. This tool facilitates symptom-based initial diagnosis of rare diseases by clinicians based on ORPHANET data set and excellent performance: ≥80% diagnostic precision, ≥99% sensitivity, and robustness to both absent and unrelated symptoms.
Computer-assisted initial diagnosis of rare diseases. Alves R, Piñol M, Vilaplana J, Teixidó I, Cruz J, Comas J, Vilaprinyo E, Sorribas A, Solsona F. PeerJ. 2016 Jul 21;4:e2211. doi: 10.7717/peerj.2211. eCollection 2016.
Automatic Methods for Carotid Contrast-Enhanced Ultrasound Imaging Quantification of Adventitial Vasa Vasorum.
Adventitial vasa vasorum are physiologic microvessels that nourish artery walls. In the presence of cardiovascular risk factors, these microvessels proliferate abnormally and are the first stage of atheromatous disease. Contrast-enhanced ultrasound (CEUS) of the carotid allows direct, quantitative and non-invasive visualization of the adventitial vasa vasorum. This tool is a computer-assisted method that speed image analysis and eliminate user subjectivity by automatic analyses and quantification of vasa vasorum neovascularization in CEUS images.This allows stratifying patients with respect to diagnostic performance. The automatic strategy is a valuable alternative to the manual Arcidiacono method, improving both diagnostic speed and diagnostic accuracy.
This program facilitates the management of people who want to quit smoking, implemented through an e-treatment software called S-PC (Smoker Patient Control). S-PC is a web-based application that manages groups of patients, provides a bidirectional communication through mobile text messages and e-mails between patients and clinicians and offers advice and control to keep track of the patients and their status.
TControl: A mobile app to follow up tobacco-quitting patients. Pifarré M, Carrera A, Vilaplana J, Cuadrado J, Solsona S, Abella F, Solsona F, Alves R. Comput Methods Programs Biomed. 2017 Apr;142:81-89. doi: 10.1016/j.cmpb.2017.02.022. Epub 2017 Feb 22.