Diagnosis support systems for rare diseases: a scoping review

Table 5 Characteristics of online tools

Tool name	Date	Data sources	Performances: Top 10 ranking	Related articles	URL
Phenomizer	2009	Phenotype concepts	NA	[63]	http://compbio.charite.de/phenomizer
BOQA	2012	Phenotype concepts	NA	[64]	http://compbio.charite.de/boqa/
Phenotips	2013	Phenotype concepts	NA	[65]	http://phenotips.org
FindZebra	2013	Phenotype concepts	63%	[66]	http://www.findzebra.com/
PhenIX	2014	Phenotype concepts/genes	~ 99%	[67]	http://compbio.charite.de/PhenIX/
Phenolyzer	2015	Phenotype concepts/genes	~ 85%	[69]	http://phenolyzer.usc.edu
RDD	2016, 2017	Phenotype concepts	38%	[2, 70]	http://diseasediscovery.udl.cat/
IEMbase	2018	Phenotype concepts	90%	[54]	http://www.iembase.org/app
PubCaseFinder	2018	Phenotype concepts	57%	[71]	https://pubcasefinder.dbcls.jp/
RDAD	2018	Phenotype concepts/genes	95%	[73]	http://www.unimd.org/RDAD/
GDDP	2019	Phenotype concepts	~ 32%	[77]	https://gddp.research.cchmc.org/
Xrare	2019	Phenotype concepts/genes	~ 95%	[78]	https://web.stanford.edu/~xm24/Xrare/
CC-Cruiser	2017	Images	NA	[44]	https://www.cc-cruiser.com/
DeepGestalt	2019	Images	NA	[62]	https://www.face2gene.com/

For each online tool, we listed the publication year, the materials used, the performance indicated in each publication, and the URLs provided in the publications. For the performance, the proportion of accurate diagnoses within the top 10 most relevant disease for each patient is given for all algorithms based on diagnoses recommendation (i.e., providing for each patient a list of potential diagnoses ranked by relevance). These results were provided by the authors of each tool and thus do not allow a comparison of tool performance, as the nature and volume of each dataset were different

ISSN: 1750-1172