R-universe search: dosimetry

Showing 4 of total 4 results (show query)

biodosetools-team

biodosetools:An R Shiny Application for Biological Dosimetry

A tool to perform all different statistical tests and calculations needed by Biological Dosimetry Laboratories. Detailed documentation is available in <https://biodosetools-team.github.io/documentation/> and the paper by Hernández et al. (2023) <doi:10.1080/09553002.2023.2176564>.

Maintained by Alfredo Hernández. Last updated 4 months ago.

biological-data dosimetry shiny-app

13.5 match 5 stars 5.20 score 16 scripts

tscnlab

LightLogR:Process Data from Wearable Light Loggers and Optical Radiation Dosimeters

Import, processing, validation, and visualization of personal light exposure measurement data from wearable devices. The package implements features such as the import of data and metadata files, conversion of common file formats, validation of light logging data, verification of crucial metadata, calculation of common parameters, and semi-automated analysis and visualization.

Maintained by Johannes Zauner. Last updated 25 days ago.

dosimetry light time-series-analysis wearable-devices wearable-sensors

10.0 match 12 stars 5.91 score 28 scripts

usepa

httk:High-Throughput Toxicokinetics

Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predictions for chemicals where in vivo data do exist. The models are systems of ordinary differential equations that are developed in MCSim and solved using compiled (C-based) code for speed. A Monte Carlo sampler is included for simulating human biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and propagating parameter uncertainty (Wambaugh et al., 2019 <doi:10.1093/toxsci/kfz205>). Empirically calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 <doi:10.1007/s10928-017-9548-7>). These functions and data provide a set of tools for using IVIVE to convert concentrations from high-throughput screening experiments (for example, Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).

Maintained by John Wambaugh. Last updated 1 months ago.

comptox ord

1.6 match 27 stars 10.22 score 307 scripts 1 dependents

cran

espadon:Easy Study of Patient DICOM Data in Oncology

Exploitation, processing and 2D-3D visualization of DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, in a patient-oriented perspective.

Maintained by Cathy Fontbonne. Last updated 1 months ago.

cpp

4.0 match 2.85 score