Additional file 1 of Radiomics to predict tumor response to combination chemoradiotherapy in squamous cell carcinoma of the anal canal: a preliminary investigation

Additional file 1: Supplementary Table S1. Acquisition parameters of pre-treatment T2-weighted TSE sequences utilized to extract radiomic features. Supplementary Fig. S1. Results of the METhodological RadiomICs Score METRICS), a quality scoring tool for radiomics research.

Institutions

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28644832
Primary Topic
Colorectal and Anal Carcinomas
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Additional file 1 of Radiomics to predict tumor response to combination chemoradiotherapy in squamous cell carcinoma of the anal canal: a preliminary investigation

Figshare
Colorectal and Anal Carcinomas
article

Additional file 1 of Radiomics to predict tumor response to combination chemoradiotherapy in squamous cell carcinoma of the anal canal: a preliminary investigation

article en

Abstract

Additional file 1: Supplementary Table S1. Acquisition parameters of pre-treatment T2-weighted TSE sequences utilized to extract radiomic features. Supplementary Fig. S1. Results of the METhodological RadiomICs Score METRICS), a quality scoring tool for radiomics research.

Figshare
Humanitas University (IT), University of Milan (IT), Fondazione IRCCS Istituto Nazionale dei Tumori (IT), New York University (US)
Good health and well-being
Openalex Percentile: Top 38%
Colorectal and Anal Carcinomas
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.