AIMC Topic: Databases, Factual

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A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Nature nanotechnology
Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a ...

Predicting severe intraventricular hemorrhage or early death using machine learning algorithms in VLBWI of the Korean Neonatal Network Database.

Scientific reports
Severe intraventricular hemorrhage (IVH) in premature infants can lead to serious neurological complications. This retrospective cohort study used the Korean Neonatal Network (KNN) dataset to develop prediction models for severe IVH or early death in...

Multi-scale 3D-CRU for EEG emotion recognition.

Biomedical physics & engineering express
In this paper, we propose a novel multi-scale 3D-CRU model, with the goal of extracting more discriminative emotion feature from EEG signals. By concurrently exploiting the relative electrode locations and different frequency subbands of EEG signals,...

Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression.

An efficient deep neural network for automatic classification of acute intracranial hemorrhages in brain CT scans.

Computers in biology and medicine
BACKGROUND: Recent advancements in deep learning models have demonstrated their potential in the field of medical imaging, achieving remarkable performance surpassing human capabilities in tasks such as classification and segmentation. However, these...

Enhancing ECG signal classification through pre-trained stacked-CNN embeddings: a transfer learning approach.

Biomedical physics & engineering express
Rapid and accurate electrocardiogram (ECG) signal classification is crucial in high-stakes healthcare settings. However, existing computational models often struggle to balance high performance with computational efficiency. This study introduces an ...

Method for Incomplete and Imbalanced Data Based on Multivariate Imputation by Chained Equations and Ensemble Learning.

IEEE journal of biomedical and health informatics
The classification analysis of incomplete and imbalanced data is still a challenging task since these issues could negatively impact the training of classifiers, which were also found in our study on the physical fitness assessments of patients. And ...

Cross-Attention Enhanced Pyramid Multi-Scale Networks for Sensor-Based Human Activity Recognition.

IEEE journal of biomedical and health informatics
Human Activity Recognition (HAR) has recently attracted widespread attention, with the effective application of this technology helping people in areas such as healthcare, smart homes, and gait analysis. Deep learning methods have shown remarkable pe...

An Efficient and Rapid Medical Image Segmentation Network.

IEEE journal of biomedical and health informatics
Accurate medical image segmentation is an essential part of the medical image analysis process that provides detailed quantitative metrics. In recent years, extensions of classical networks such as UNet have achieved state-of-the-art performance on m...