Radiomics beyond the hype: a critical evaluation toward oncologic clinical use
Radiomics is a promising and fast-develo** field within oncology that involves the mining
of quantitative high-dimensional data from medical images. Radiomics has the potential to …
of quantitative high-dimensional data from medical images. Radiomics has the potential to …
The accuracy and quality of image-based artificial intelligence for muscle-invasive bladder cancer prediction
C He, H Xu, E Yuan, L Ye, Y Chen, J Yao, B Song - Insights into Imaging, 2024 - Springer
Purpose To evaluate the diagnostic performance of image-based artificial intelligence (AI)
studies in predicting muscle-invasive bladder cancer (MIBC).(2) To assess the reporting …
studies in predicting muscle-invasive bladder cancer (MIBC).(2) To assess the reporting …
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Purpose To propose a new quality scoring tool, METhodological RadiomICs Score
(METRICS), to assess and improve research quality of radiomics studies. Methods We …
(METRICS), to assess and improve research quality of radiomics studies. Methods We …
[HTML][HTML] Consolidated reporting guidelines for prognostic and diagnostic machine learning modeling studies: development and validation
Background The reporting of machine learning (ML) prognostic and diagnostic modeling
studies is often inadequate, making it difficult to understand and replicate such studies. To …
studies is often inadequate, making it difficult to understand and replicate such studies. To …
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Despite major advances in artificial intelligence (AI) research for healthcare, the deployment
and adoption of AI technologies remain limited in clinical practice. This paper describes the …
and adoption of AI technologies remain limited in clinical practice. This paper describes the …
[HTML][HTML] Pitfalls in develo** machine learning models for predicting cardiovascular diseases: challenge and solutions
YQ Cai, DX Gong, LY Tang, Y Cai, HJ Li… - Journal of Medical …, 2024 - jmir.org
In recent years, there has been explosive development in artificial intelligence (AI), which
has been widely applied in the health care field. As a typical AI technology, machine …
has been widely applied in the health care field. As a typical AI technology, machine …
Reproducibility of radiomics quality score: an intra-and inter-rater reliability study
Objectives To investigate the intra-and inter-rater reliability of the total radiomics quality
score (RQS) and the reproducibility of individual RQS items' score in a large multireader …
score (RQS) and the reproducibility of individual RQS items' score in a large multireader …
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
Although artificial intelligence (AI) methods hold promise for medical imaging-based
prediction tasks, their integration into medical practice may present a double-edged sword …
prediction tasks, their integration into medical practice may present a double-edged sword …
Towards reproducible radiomics research: introduction of a database for radiomics studies
Objectives To investigate the model-, code-, and data-sharing practices in the current
radiomics research landscape and to introduce a radiomics research database. Methods A …
radiomics research landscape and to introduce a radiomics research database. Methods A …
Towards reproducible radiomics research: introduction of a database for radiomics studies
Objectives To investigate the model-, code-, and data-sharing practices in the current
radiomics research landscape and to introduce a radiomics research database. Methods A …
radiomics research landscape and to introduce a radiomics research database. Methods A …