AIMC Topic: Flow Cytometry
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Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data.
Scientific reports
Apr 23, 2024
Myelodysplastic syndrome is primarily characterized by dysplasia in the bone marrow (BM), presenting a challenge in consistent morphology interpretation. Accurate diagnosis through traditional slide-based analysis is difficult, necessitating a standa...
Deep learning-enabled detection of rare circulating tumor cell clusters in whole blood using label-free, flow cytometry.
Lab on a chip
Apr 16, 2024
Metastatic tumors have poor prognoses for progression-free and overall survival for all cancer patients. Rare circulating tumor cells (CTCs) and rarer circulating tumor cell clusters (CTCCs) are potential biomarkers of metastatic growth, with CTCCs r...
Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube.
Scientific reports
Apr 9, 2024
This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cyto...
Machine learning aided single cell image analysis improves understanding of morphometric heterogeneity of human mesenchymal stem cells.
Methods (San Diego, Calif.)
Mar 13, 2024
The multipotent stem cells of our body have been largely harnessed in biotherapeutics. However, as they are derived from multiple anatomical sources, from different tissues, human mesenchymal stem cells (hMSCs) are a heterogeneous population showing ...
Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation.
Analytical chemistry
Mar 6, 2024
Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC techno...
MAGIC-DR: An interpretable machine-learning guided approach for acute myeloid leukemia measurable residual disease analysis.
Cytometry. Part B, Clinical cytometry
Feb 28, 2024
Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but...
Recommendations for using artificial intelligence in clinical flow cytometry.
Cytometry. Part B, Clinical cytometry
Feb 26, 2024
Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditionally requires close inspection of digital data by hematopathologists with expert domain knowledge. Advances in artificial intelligence (AI) are trans...
Translating the regulatory landscape of medical devices to create fit-for-purpose artificial intelligence (AI) cytometry solutions.
Cytometry. Part B, Clinical cytometry
Feb 23, 2024
The implementation of medical software and artificial intelligence (AI) algorithms into routine clinical cytometry diagnostic practice requires a thorough understanding of regulatory requirements and challenges throughout the cytometry software produ...
Convolutional neuronal network for identifying single-cell-platelet-platelet-aggregates in human whole blood using imaging flow cytometry.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Feb 15, 2024
Imaging flow cytometry is an attractive method to investigate individual cells by optical properties. However, imaging flow cytometry applications with clinical relevance are scarce so far. Platelet aggregation naturally occurs during blood coagulati...
Leukocyte differential based on an imaging and impedance flow cytometry of microfluidics coupled with deep neural networks.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jan 4, 2024
The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitations of low throughputs in classifying leukocytes while commercially available hematology analyzers f...
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