Medicine
Life Sciences
Field Statistics
Total Projects: 40
Average Confidence:
63%
High Confidence (≥70%): 18
Medium Confidence (50-70%): 4
Low Confidence (<50%): 18
Field Keywords:
Common Packages:
Scientific Indicators:
Top Keywords from Projects
Related Fields
- Biology (100 projects)
- Biochemistry, Genetics and Molecular Biology (16 projects)
- Agricultural and Biological Sciences (17 projects)
- Neuroscience (23 projects)
Projects in Medicine (40)
Intracranial Electrode Location and Analysis in MNE-Python 92% confidence
Intracranial Electrode Location and Analysis in MNE-Python - Published in JOSS (2022)
100%
fRAT 88% confidence
fRAT: an interactive, Python-based tool for region-of-interest summaries of functional imaging data - Published in JOSS (2023)
100%
fMRIStroke 88% confidence
fMRIStroke: A preprocessing pipeline for fMRI Data from Stroke patients - Published in JOSS (2024)
Also in: Economics, Sociology93%
MNE-BIDS 88% confidence
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis - Published in JOSS (2019)
100%
xcp_d 88% confidence
Post-processing of fMRIPrep, NiBabies, and HCP outputs
Also in: Sociology, Mathematics67%
PyBispectra 84% confidence
PyBispectra: A toolbox for advanced electrophysiological signal processing using the bispectrum - Published in JOSS (2025)
98%
MNE-LSL 84% confidence
MNE-LSL: Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices. - Published in JOSS (2025)
100%
Giga Connectome 84% confidence
Giga Connectome: a BIDS-app for time series and functional connectome extraction - Published in JOSS (2025)
Also in: Mathematics, Artificial Intelligence and Machine Learning98%
SleepECG 84% confidence
SleepECG: a Python package for sleep staging based on heart rate - Published in JOSS (2023)
93%
Frites 84% confidence
Frites: A Python package for functional connectivity analysis and group-level statistics of neurophysiological data - Published in JOSS (2022)
100%
MNELAB 84% confidence
MNELAB: a graphical user interface for MNE-Python - Published in JOSS (2022)
95%
MNE-ICALabel 84% confidence
MNE-ICALabel: Automatically annotating ICA components with ICLabel in Python - Published in JOSS (2022)
98%
Octopus Sensing 84% confidence
Octopus Sensing: A Python library for human behavior studies - Published in JOSS (2022)
95%
FURY 84% confidence
FURY: advanced scientific visualization - Published in JOSS (2021)
95%
pd-parser 84% confidence
pd-parser: A tool for Matching Photodiode Deflection Events to Time-Stamped Events - Published in JOSS (2020)
Also in: Neuroscience, Mathematics93%
NeuroDSP 84% confidence
NeuroDSP: A package for neural digital signal processing - Published in JOSS (2019)
Also in: Mathematics100%
AtlasReader 84% confidence
AtlasReader: A Python package to generate coordinate tables, region labels, and informative figures from statistical MRI images - Published in JOSS (2019)
Also in: Artificial Intelligence and Machine Learning100%
QUIT 84% confidence
QUIT: QUantitative Imaging Tools - Published in JOSS (2018)
Also in: Neuroscience95%
SurPyval 63% confidence
SurPyval: Survival Analysis with Python - Published in JOSS (2021)
93%
MiTfAT 63% confidence
MiTfAT: A Python-based Analysis Tool for Molecular fMRI Experiments. - Published in JOSS (2021)
100%
FIPS 60% confidence
FIPS: An R Package for Biomathematical Modelling of Human Fatigue Related Impairment - Published in JOSS (2020)
95%
dia 60% confidence
dia: An R package for the National Oceanic and Atmospheric Administration dam impact analysis - Published in JOSS (2025)
95%
coder 45% confidence
coder: An R package for code-based item classification and categorization - Published in JOSS (2020)
93%
PyMSM 45% confidence
PyMSM: Python package for Competing Risks and Multi-State models for Survival Data - Published in JOSS (2022)
Also in: Engineering, Artificial Intelligence and Machine Learning98%
Fitting a Gamma-Gompertz survival model to capture-recapture data collected on free-ranging animal populations 40% confidence
Fitting a Gamma-Gompertz survival model to capture-recapture data collected on free-ranging animal populations - Published in JOSS (2018)
95%
NEMSEER 40% confidence
NEMSEER: A Python package for downloading and handling historical National Electricity Market forecast data produced by the Australian Energy Market Operator - Published in JOSS (2023)
100%
Mozzie 40% confidence
Mozzie: a computationally efficient simulator for the spatio-temporal modelling of mosquitoes - Published in JOSS (2025)
Also in: Materials Science, Agricultural and Biological Sciences98%
ExpFamilyPCA.jl 40% confidence
ExpFamilyPCA.jl: A Julia Package for Exponential Family Principal Component Analysis - Published in JOSS (2025)
100%
RxInfer 40% confidence
RxInfer: A Julia package for reactive real-time Bayesian inference - Published in JOSS (2023)
77%
shinyssd v1.0 40% confidence
shinyssd v1.0: Species Sensitivity Distributions for Ecotoxicological Risk Assessment - Published in JOSS (2019)
67%
netrankr 40% confidence
netrankr: An R package for total, partial, and probabilistic rankings in networks - Published in JOSS (2022)
100%
tipr 40% confidence
tipr: An R package for sensitivity analyses for unmeasured confounders - Published in JOSS (2022)
Also in: Earth and Environmental Sciences, Engineering49%
ElGateau 40% confidence
ElGateau: A Library for Using the Elgato Stream Deck for Experimental Psychology Research - Published in JOSS (2018)
93%
36%
funsies 40% confidence
funsies: A minimalist, distributed and dynamic workflow engine - Published in JOSS (2021)
98%
StochasticDominance.jl 40% confidence
StochasticDominance.jl: A Julia Package for Higher Order Stochastic Dominance - Published in JOSS (2025)
36%
splithalf 40% confidence
splithalf: robust estimates of split half reliability - Published in JOSS (2021)
Also in: Neuroscience, Artificial Intelligence and Machine Learning95%
presize 40% confidence
presize: An R-package for precision-based sample size calculation in clinical research - Published in JOSS (2021)
93%
CoPro 40% confidence
CoPro: a data-driven modelling framework for conflict risk projections - Published in JOSS (2021)
98%