Baselinev3

About

Creators:

niebieskamarchewka

piotr.wawryka

kprzystalski

Contact email:

kprzystalski@gmail.com

Image Version:

6f728d1d-0cb7-4f07-a8d1-b8178eafa573

Last updated:

Jan. 15, 2024, 7:40 p.m.

Interfaces

This algorithm implements all of the following input-output combinations:

Inputs Outputs

	Inputs	Outputs
1	Axial T2 Prostate MRI Description Axial T2 MRI of the Prostate Kind Image Read from `/input/images/axial-t2-prostate-mri/<uuid>.mha` or `/input/images/axial-t2-prostate-mri/<uuid>.tif` Axial T2 Prostate MRI PSA and Age Description JSON document containing the propetries "patient_age" (integer) and "psa" in ng/mL (number). Kind Anything Read from `/input/psa-and-age.json` Example { "key": "value", "None": null } PSA and Age	Prostate Cancer Risk Score Description Prostate Cancer Risk Score with values "Low" or "High" Kind String Write to `/output/prostate-cancer-risk-score.json` Example "Example String" Prostate Cancer Risk Score Prostate Cancer Risk Score Likelihood Description Prostate Cancer Risk Score Likelihood with values between 0 and 1 Kind Float Write to `/output/prostate-cancer-risk-score-likelihood.json` Example 42.0 Prostate Cancer Risk Score Likelihood

Challenge Performance

Date	Challenge	Phase	Rank
Jan. 15, 2024	CHAIMELEON	Test Prostate Classification	27

Model Facts

Summary

3d CNN

Mechanism

3d CNN

Validation and Performance

3d CNN

Uses and Directions

This algorithm was developed for research purposes only.

Warnings

Left empty by the Algorithm Editors

Common Error Messages

Left empty by the Algorithm Editors

Information on this algorithm has been provided by the Algorithm Editors, following the Model Facts labels guidelines from Sendak, M.P., Gao, M., Brajer, N. et al. Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3