AIMC Topic: Leukocytes, Mononuclear
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Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.
Methods in cell biology
Sep 15, 2023
Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large amount of patient cells. To maximize information from and minimize the need of precious samples in ca...
Low-Latency In Situ Image Analytics With FPGA-Based Quantized Convolutional Neural Network.
IEEE transactions on neural networks and learning systems
Jul 6, 2022
Real-time in situ image analytics impose stringent latency requirements on intelligent neural network inference operations. While conventional software-based implementations on the graphic processing unit (GPU)-accelerated platforms are flexible and ...
SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning.
Genome biology
Jun 20, 2022
The COVID-19 pandemic has emphasized the importance of accurate detection of known and emerging pathogens. However, robust characterization of pathogenic sequences remains an open challenge. To address this need we developed SeqScreen, which accurate...
Reversing radiation-induced immunosuppression using a new therapeutic modality.
Life sciences in space research
May 11, 2022
Radiation-induced immune suppression poses significant health challenges for millions of patients undergoing cancer chemotherapy and radiotherapy treatment, and astronauts and space tourists travelling to outer space. While a limited number of recomb...
Validation of a deep learning-based image analysis system to diagnose subclinical endometritis in dairy cows.
PloS one
Jan 28, 2022
The assessment of polymorphonuclear leukocyte (PMN) proportions (%) of endometrial samples is the hallmark for subclinical endometritis (SCE) diagnosis. Yet, a non-biased, automated diagnostic method for assessing PMN% in endometrial cytology slides ...
Advanced Deep Learning Human Herpes Virus 6 (HHV-6) Molecular Detection in Understanding Human Infertility.
Computational intelligence and neuroscience
Jan 7, 2022
To see if HHV-6 may be a cause of infertility, researchers looked at 18 men and 10 women who had unexplained critical fertility and had at least one prior pregnancy. HHV-6 DNA was discovered in both infertile and fertile peripheral blood mononuclear ...
A weakly supervised deep learning approach for label-free imaging flow-cytometry-based blood diagnostics.
Cell reports methods
Oct 25, 2021
The application of machine learning approaches to imaging flow cytometry (IFC) data has the potential to transform the diagnosis of hematological diseases. However, the need for manually labeled single-cell images for machine learning model training ...
Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection.
Scientific reports
Oct 15, 2021
Accurate detection and risk stratification of latent tuberculosis infection (LTBI) remains a major clinical and public health problem. We hypothesize that multiparameter strategies that probe immune responses to Mycobacterium tuberculosis can provide...
An active learning approach for clustering single-cell RNA-seq data.
Laboratory investigation; a journal of technical methods and pathology
Jul 9, 2021
Single-cell RNA sequencing (scRNA-seq) data has been widely used to profile cellular heterogeneities with a high-resolution picture. Clustering analysis is a crucial step of scRNA-seq data analysis because it provides a chance to identify and uncover...
Hierarchical progressive learning of cell identities in single-cell data.
Nature communications
May 14, 2021
Supervised methods are increasingly used to identify cell populations in single-cell data. Yet, current methods are limited in their ability to learn from multiple datasets simultaneously, are hampered by the annotation of datasets at different resol...
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