The "intelligent workstation" for cell-surface phenotyping based on principles of pattern recognition and image analysis.
Technical advancements in computer hardware and the associated computerized architectures allow the design and fabrication of dedicated, modestly expensive computerized workstations to aid humans in complex decision-making tasks. We refer to these as "Intelligent Workstations" because they accommodate the hypothesis-driven reasoning ability of the user into the system. Concomitant with the rapid developments in computers, diagnostic and therapeutic technologies related to cell analysis have undergone growth. Combining these technologies requires careful formulation and analysis of the diagnostic model involving image cytometry. Here we present a model of the intelligent workstation for image cytometry and illustrate its advantages in cell-surface phenotyping. Combining cell morphology with cell-surface phenotyping has clear diagnostic utility that no other widely available methods can supply. Although the reported results are based on samples of peripheral blood, cell suspensions of disaggregated cells can also be analyzed.
Goin
J E
JE
Craven
T M
TM
Gilbert
J R
JR
Melnicoff
M J
MJ
Tomaszewski
J E
JE
Wilding
P
P
D000368:Aged; D000911:Antibodies, Monoclonal; D000954:Antigens, Surface / Q000032:analysis*; D001185:Artificial Intelligence; D001322:Autoanalysis; D001772:Blood Cell Count / Q000295:instrumentation; D002051:Burkitt Lymphoma / Q000097:blood; D003201:Computers; D005260:Female; D005434:Flow Cytometry / Q000379:methods; D006801:Humans; D007945:Leukemia, Lymphoid / Q000097:blood; D007958:Leukocyte Count; D010641:Phenotype
D000911:Antibodies, Monoclonal; D000954:Antigens, Surface