AIMC Topic: Algorithms

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Real-time fluorescence imaging flow cytometry enabled by motion deblurring and deep learning algorithms.

Lab on a chip
Fluorescence imaging flow cytometry (IFC) has been demonstrated as a crucial biomedical technique for analyzing specific cell subpopulations from heterogeneous cellular populations. However, the high-speed flow of fluorescent cells leads to motion bl...

Machine learning for lumbar and pelvis kinematics clustering.

Computer methods in biomechanics and biomedical engineering
Clustering algorithms such as k-means and agglomerative hierarchical clustering (HCA) may provide a unique opportunity to analyze time-series kinematic data. Here we present an approach for determining number of clusters and which clustering algorith...

An advanced deep learning method to detect and classify diabetic retinopathy based on color fundus images.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
BACKGROUND: In this article, we present a computerized system for the analysis and assessment of diabetic retinopathy (DR) based on retinal fundus photographs. DR is a chronic ophthalmic disease and a major reason for blindness in people with diabete...

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework.

Nature genetics
Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals...

High-Order Correlation-Guided Slide-Level Histology Retrieval With Self-Supervised Hashing.

IEEE transactions on pattern analysis and machine intelligence
Histopathological Whole Slide Images (WSIs) play a crucial role in cancer diagnosis. It is of significant importance for pathologists to search for images sharing similar content with the query WSI, especially in the case-based diagnosis. While slide...

Optimized Classifier Learning for Face Recognition Performance Boost in Security and Surveillance Applications.

Sensors (Basel, Switzerland)
Face recognition has become an integral part of modern security processes. This paper introduces an optimization approach for the quantile interval method (QIM), a promising classifier learning technique used in face recognition to create face templa...

Metadata and Image Features Co-Aware Personalized Federated Learning for Smart Healthcare.

IEEE journal of biomedical and health informatics
Recently, artificial intelligence has been widely used in intelligent disease diagnosis and has achieved great success. However, most of the works mainly rely on the extraction of image features but ignore the use of clinical text information of pati...

Semi-Supervised Medical Image Segmentation With Voxel Stability and Reliability Constraints.

IEEE journal of biomedical and health informatics
Semi-supervised learning is becoming an effective solution in medical image segmentation because annotations are costly and tedious to acquire. Methods based on the teacher-student model use consistency regularization and uncertainty estimation and h...

Characterization of Synthetic Health Data Using Rule-Based Artificial Intelligence Models.

IEEE journal of biomedical and health informatics
The aim of this study is to apply and characterize eXplainable AI (XAI) to assess the quality of synthetic health data generated using a data augmentation algorithm. In this exploratory study, several synthetic datasets are generated using various co...

Domain Agnostic Post-Processing for QRS Detection Using Recurrent Neural Network.

IEEE journal of biomedical and health informatics
Deep-learning-based QRS-detection algorithms often require essential post-processing to refine the output prediction-stream for R-peak localisation. The post-processing involves basic signal-processing tasks including the removal of random noise in t...