Medical long-tailed learning for imbalanced data: bibliometric analysis
Background In the last decade, long-tail learning has become a popular research focus in
deep learning applications in medicine. However, no scientometric reports have provided a …
deep learning applications in medicine. However, no scientometric reports have provided a …
An omics-to-omics joint knowledge association subtensor model for radiogenomics cross-modal modules from genomics and ultrasonic images of breast cancers
J Xi, D Sun, C Chang, S Zhou, Q Huang - Computers in Biology and …, 2023 - Elsevier
The radiogenomics analysis can provide the connections between genomics and radiomics,
which can infer the genomic features of tumors from their radiogenomic associations through …
which can infer the genomic features of tumors from their radiogenomic associations through …
[Retracted] A Machine Learning Model for Early Prediction and Detection of Sepsis in Intensive Care Unit Patients
In today's scenario, sepsis is impacting millions of patients in the intensive care unit due to
the fact that the mortality rate is increased exponentially and has become a major challenge …
the fact that the mortality rate is increased exponentially and has become a major challenge …
Coronary heart disease prediction method fusing domain-adaptive transfer learning with graph convolutional networks (GCN)
H Lin, K Chen, Y Xue, S Zhong, L Chen, M Ye - Scientific Reports, 2023 - nature.com
Graph convolutional networks (GCNs) have achieved impressive results in many medical
scenarios involving graph node classification tasks. However, there are difficulties in transfer …
scenarios involving graph node classification tasks. However, there are difficulties in transfer …
Decisions are not all equal—Introducing a utility metric based on case-wise raters' perceptions
Abstract Background and Objective Evaluation of AI-based decision support systems (AI-
DSS) is of critical importance in practical applications, nonetheless common evaluation …
DSS) is of critical importance in practical applications, nonetheless common evaluation …
The impact of recency and adequacy of historical information on sepsis predictions using machine learning
Sepsis is a major public and global health concern. Every hour of delay in detecting sepsis
significantly increases the risk of death, highlighting the importance of accurately predicting …
significantly increases the risk of death, highlighting the importance of accurately predicting …
Feature augmentation and semi-supervised conditional transfer learning for early detection of sepsis
Early detection of Sepsis is crucial for improving patient outcomes, as it is a significant public
health concern that results in substantial morbidity and mortality. However, despite the …
health concern that results in substantial morbidity and mortality. However, despite the …
Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers
G Zhang, F Shao, W Yuan, J Wu, X Qi, J Gao… - European Journal of …, 2024 - Springer
Background This study aimed to develop and validate an interpretable machine-learning
model that utilizes clinical features and inflammatory biomarkers to predict the risk of in …
model that utilizes clinical features and inflammatory biomarkers to predict the risk of in …
[HTML][HTML] Embedding-based terminology expansion via secondary use of large clinical real-world datasets
A log-likelihood based co-occurrence analysis of∼ 1.9 million de-identified ICD-10 codes
and related short textual problem list entries generated possible term candidates at a …
and related short textual problem list entries generated possible term candidates at a …
A comprehensive machine learning based pipeline for an accurate early prediction of sepsis in ICU
Sepsis is a lethal infection-related illness that has an extremely high fatality rate, especially
among intensive care unit patients. Early and precise recognition of sepsis is critical as …
among intensive care unit patients. Early and precise recognition of sepsis is critical as …