AIMC Topic: Algorithms

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Knowledge graph revision in the context of unknown knowledge.

PloS one
The role of knowledge graph encompasses the representation, organization, retrieval, reasoning, and application of knowledge, providing a rich and robust cognitive foundation for artificial intelligence systems and applications. When we learn new thi...

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

PloS one
To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the...

DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model.

Medical & biological engineering & computing
Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introd...

Artificial intelligence for detection of prostate cancer in biopsies during active surveillance.

BJU international
OBJECTIVES: To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active surveillance (AS).

Accelerated High-Resolution Deep Learning Reconstruction Turbo Spin Echo MRI of the Knee at 7 T.

Investigative radiology
OBJECTIVES: The aim of this study was to compare the image quality of 7 T turbo spin echo (TSE) knee images acquired with varying factors of parallel-imaging acceleration reconstructed with deep learning (DL)-based and conventional algorithms.

Multi-scale object equalization learning network for intracerebral hemorrhage region segmentation.

Neural networks : the official journal of the International Neural Network Society
Segmentation and the subsequent quantitative assessment of the target object in computed tomography (CT) images provide valuable information for the analysis of intracerebral hemorrhage (ICH) pathology. However, most existing methods lack a reasonabl...

Language-aware multiple datasets detection pretraining for DETRs.

Neural networks : the official journal of the International Neural Network Society
Pretraining on large-scale datasets can boost the performance of object detectors while the annotated datasets for object detection are hard to scale up due to the high labor cost. What we possess are numerous isolated filed-specific datasets, thus, ...

Ensemble learning algorithms to elucidate the core microbiome's impact on carbon content and degradation properties at the soil aggregate level.

The Science of the total environment
Soil aggregates are crucial for soil organic carbon (OC) accumulation. This study, utilizing a 32-year fertilization experiment, investigates whether the core microbiome can elucidate variations in carbon content and decomposition across different ag...

ALFREDO: Active Learning with FeatuRe disEntangelement and DOmain adaptation for medical image classification.

Medical image analysis
State-of-the-art deep learning models often fail to generalize in the presence of distribution shifts between training (source) data and test (target) data. Domain adaptation methods are designed to address this issue using labeled samples (supervise...

CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning usually achieves good performance in the supervised way, which requires a large amount of labeled data. However, manual labeling of electrocardiograms (ECGs) is laborious that requires much medical knowledge. S...