External validation of prognostic models: what, why, how, when and where?
Prognostic models that aim to improve the prediction of clinical events, individualized
treatment and decision-making are increasingly being developed and published. However …
treatment and decision-making are increasingly being developed and published. However …
Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis
A Zwanenburg - European journal of nuclear medicine and molecular …, 2019 - Springer
Radiomics in nuclear medicine is rapidly expanding. Reproducibility of radiomics studies in
multicentre settings is an important criterion for clinical translation. We therefore performed a …
multicentre settings is an important criterion for clinical translation. We therefore performed a …
Restaurant survival prediction using customer-generated content: An aspect-based sentiment analysis of online reviews
Business failure prediction or survival analysis can assist corporate organizations in better
understanding their performance and improving decision making. Based on aspect-based …
understanding their performance and improving decision making. Based on aspect-based …
scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn
S Pölsterl - Journal of Machine Learning Research, 2020 - jmlr.org
scikit-survival is an open-source Python package for time-to-event analysis fully compatible
with scikit-learn. It provides implementations of many popular machine learning techniques …
with scikit-learn. It provides implementations of many popular machine learning techniques …
Sybil: a validated deep learning model to predict future lung cancer risk from a single low-dose chest computed tomography
PURPOSE Low-dose computed tomography (LDCT) for lung cancer screening is effective,
although most eligible people are not being screened. Tools that provide personalized …
although most eligible people are not being screened. Tools that provide personalized …
[HTML][HTML] Prognosis of patients with hepatocellular carcinoma treated with immunotherapy–development and validation of the CRAFITY score
B Scheiner, K Pomej, MM Kirstein, F Hucke… - Journal of …, 2022 - Elsevier
Background & Aims Immunotherapy with atezolizumab plus bevacizumab represents the
new standard of care in systemic front-line treatment of hepatocellular carcinoma (HCC) …
new standard of care in systemic front-line treatment of hepatocellular carcinoma (HCC) …
Deep learning-based classification of mesothelioma improves prediction of patient outcome
Malignant mesothelioma (MM) is an aggressive cancer primarily diagnosed on the basis of
histological criteria. The 2015 World Health Organization classification subdivides …
histological criteria. The 2015 World Health Organization classification subdivides …
Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy
INTRODUCTION Aneuploidy, also known as somatic copy number alterations (SCNAs), is
widespread in human cancers and has been proposed to drive tumorigenesis. The …
widespread in human cancers and has been proposed to drive tumorigenesis. The …
Toward robust mammography-based models for breast cancer risk
Improved breast cancer risk models enable targeted screening strategies that achieve
earlier detection and less screening harm than existing guidelines. To bring deep learning …
earlier detection and less screening harm than existing guidelines. To bring deep learning …
ECG-based deep learning and clinical risk factors to predict atrial fibrillation
Background: Artificial intelligence (AI)–enabled analysis of 12-lead ECGs may facilitate
efficient estimation of incident atrial fibrillation (AF) risk. However, it remains unclear whether …
efficient estimation of incident atrial fibrillation (AF) risk. However, it remains unclear whether …