Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95)

Comparison of osteoconductive properties of three different ß-tricalcium phosphate graft materials: A pilot histomorphometric study in a pig model

PubMedID: 25491275Aims The aim of this study was to compare the de novo bone formation ability and osteoconductive effects of three different ß-tricalcium phosphate (ß-TCP) graft materials. The micro-Architectural parameters of the newly formed bone tissues were also compared among the different graft materials. Material and methods Eight male Swiss domestic pigs were used in the study. Five bony defects were made with a trephine bur. Three of the defects were filled with Cerasorb®, Kasios® and Poresorb®. The fourth defect was filled with an autogenous bone graft. The last defect remained empty. All subjects were sacrificed after 8 weeks. Results When compared to a negative control group, significant healing was observed in all the groups except the Cerasorb group. The osteoconductivity of the Poresorb group was better than that of the other groups (p < 0.05). The difference in the osteoconductivity of the Kasios and Cerasorb groups was statistically significant (p < 0.05). Comparison of the micro-Architectural properties of newly formed bone tissues retrieved from the defects showed that those filled with Poresorb were the best. Conclusion ß-TCP materials show different results in terms of the volume and characteristics of new bone formation, although they have a similar chemical structure. © 2014 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved

Crowdsourcing digital health measures to predict Parkinson’s disease severity: The Parkinson’s Disease Digital Biomarker DREAM Challenge.

Consumer wearables and sensors are a rich source of data about patients’ daily disease and symptom burden, particularly in the case of movement disorders like Parkinson’s disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95)

The prevalence of childhood psychopathology in Turkey: a cross-sectional multicenter nationwide study (EPICPAT-T)

PMID = 3096438