Tool to analyze and evaluate multi-dimensional data used in medical and research facilities
The graphs, tables and reports shown are from real studies, thereby the owners have limited their visibility for confidentiality reasons
SciDataAnalyzer arises as a result of a work of support and improvement of research for IDIVAL. A study and analysis of the work methodologies and scientific production of a team of doctors and researchers related to the field of health is carried out. Once the workflows have been analyzed, a tool is designed and developed capable of facilitating the analysis and interpretation of the results.
A set of widgets (dialog programming) and processing modules (MATA, SciDataAnalyzer libraries) are developed that act as connectors with the SciDataAnalyzer runtime. The researcher receives data simplifications and an usable interface to index and incorporate the different data sources and their forms of processing. The runtime is responsible for orchestrating the interaction between the backend, the databases and the inputs. Finally, the tool offers processed data, representations and graphs that facilitate the analysis of the data, as well as a convenient selection of reports and outputs to the system that can be consumed by other applications (R, excel, latex), as can be seen in the following captures.
SciDataAnalyzer supports and facilitates the interpretation and publication of multiple types of survival analyzes and pure statistical methods, such as regressions used in clinical, cohort or case-control studies. Taking into account the current backend, we have developed and optimized Kaplan-Meier, Cox, Weibull, exponential, relative survival and synthesization studies such as meta-analysis, in addition to linear, logistic and multinomial regressions.
The reports and assets generated have been used in many research projects and studies, in addition to the daily work of the scientific team. They have served to analyze and evaluate studies of genetic susceptibility, ultra-violet radiation, effects of diets, epistasis, osteoarthritis, reproductive factors as well as different types of cancer.
Group4Layers had developed and optimized scientific libraries used in medical fields, even parallelizing applications implemented with R, accelerating the execution of programs made with high-level statistical languages. Thanks to these efforts and previous experience, Stata specialized teams have requested our consulting work since the beginning of 2017.
Group4Layers can help you
Do you want us to analyze and offer solutions to improve the research productivity of your team? Do you need your programs and libraries to compute faster? Would you like to simplify the process of experimentation and analysis of your research?