artificial neural network (ann) model-development tool Search Results


neuralworks professional ii plus  (NeuralWare Inc)
90
NeuralWare Inc neuralworks professional ii plus
Neuralworks Professional Ii Plus, supplied by NeuralWare Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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artificial neural networks (ann)  (MathWorks Inc)
90
MathWorks Inc artificial neural networks (ann)
Artificial Neural Networks (Ann), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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artificial neural network model  (MathWorks Inc)
90
MathWorks Inc artificial neural network model
Artificial Neural Network Model, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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neural fitting tool  (MathWorks Inc)
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MathWorks Inc neural fitting tool
Neural Fitting Tool, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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multilayer perceptron artificial neural network algorithm  (MathWorks Inc)
90
MathWorks Inc multilayer perceptron artificial neural network algorithm
Multilayer Perceptron Artificial Neural Network Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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artificial neural network (ann) models  (MicroFluidic Systems)
90
MicroFluidic Systems artificial neural network (ann) models
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
Artificial Neural Network (Ann) Models, supplied by MicroFluidic Systems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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artificial neural network (ann) models - by Bioz Stars, 2026-04
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neurosolution ® software  (NeuroDimension Inc)
90
NeuroDimension Inc neurosolution ® software
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
Neurosolution ® Software, supplied by NeuroDimension Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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neurosolution ® software - by Bioz Stars, 2026-04
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simcyp simulator  (Simcyp)
90
Simcyp simcyp simulator
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
Simcyp Simulator, supplied by Simcyp, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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simulink model development  (MathWorks Inc)
90
MathWorks Inc simulink model development
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
Simulink Model Development, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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r studio version 1.3  (RStudio)
90
RStudio r studio version 1.3
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
R Studio Version 1.3, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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model development procedure  (DataRobot Inc)
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DataRobot Inc model development procedure
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
Model Development Procedure, supplied by DataRobot Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matlab software  (MathWorks Inc)
90
MathWorks Inc matlab software
Schematic illustration of the generation of <t>monodisperse</t> <t>PLGA</t> droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train <t>ANN</t> models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.
Matlab Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Schematic illustration of the generation of monodisperse PLGA droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train ANN models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.

Journal: Scientific Reports

Article Title: Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

doi: 10.1038/s41598-020-76477-5

Figure Lengend Snippet: Schematic illustration of the generation of monodisperse PLGA droplets either in a single emulsion format by single junction devices ( A ) or microfluidic devices with seven parallel junctions ( B ), or in a multiple emulsion format ( C ) by two sequentially coupled devices. Generated droplets were imaged at the orifice of the flow-focusing region in the microfluidic chips. Data generated were thereafter used to train ANN models. Schematic of one of the developed models (ANN-ABC) ( D ). AP aqueous phase, FR flow rate.

Article Snippet: These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged.

Techniques: Emulsion, Generated

Correlation between observed and predicted droplet/particle size generated by 3D flow focusing droplet chip with a single junction. Results obtained from the developed ANN-A model implemented by Statistica v13.3. Results shown for the developed ANN-A model for the training, test, validation, and external datasets. The reported r 2 values were calculated for each dataset including droplets and microparticles data.

Journal: Scientific Reports

Article Title: Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

doi: 10.1038/s41598-020-76477-5

Figure Lengend Snippet: Correlation between observed and predicted droplet/particle size generated by 3D flow focusing droplet chip with a single junction. Results obtained from the developed ANN-A model implemented by Statistica v13.3. Results shown for the developed ANN-A model for the training, test, validation, and external datasets. The reported r 2 values were calculated for each dataset including droplets and microparticles data.

Article Snippet: These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged.

Techniques: Generated, Biomarker Discovery

Correlation between experimentally observed and predicted droplet/particle size generated by the flow focusing droplet chip with 7 junctions operating in parallel. Results obtained from ANN-B model implemented by Statistica v13.3. Data shown for Training, test, validation, and external datasets. The reported r 2 values were calculated for each dataset including droplets and microparticles data.

Journal: Scientific Reports

Article Title: Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

doi: 10.1038/s41598-020-76477-5

Figure Lengend Snippet: Correlation between experimentally observed and predicted droplet/particle size generated by the flow focusing droplet chip with 7 junctions operating in parallel. Results obtained from ANN-B model implemented by Statistica v13.3. Data shown for Training, test, validation, and external datasets. The reported r 2 values were calculated for each dataset including droplets and microparticles data.

Article Snippet: These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged.

Techniques: Generated, Biomarker Discovery

Correlation between observed and predicted droplet/particle size generated by two consecutive cross-junctions featuring flow focusing microfluidic chips placed in series obtained from ANN-C model implemented by Statistica v13.3. Data are shown for training, test, validation, and external datasets.

Journal: Scientific Reports

Article Title: Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

doi: 10.1038/s41598-020-76477-5

Figure Lengend Snippet: Correlation between observed and predicted droplet/particle size generated by two consecutive cross-junctions featuring flow focusing microfluidic chips placed in series obtained from ANN-C model implemented by Statistica v13.3. Data are shown for training, test, validation, and external datasets.

Article Snippet: These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged.

Techniques: Generated, Biomarker Discovery

Correlation between observed and predicted droplet/particle sizes with the corresponding r 2 values obtained from the developed ANN-ABC model implemented by Statistica v13.3. Correlations are shown for the training, test, validation and, external datasets for three types of microfluidic systems: MFS A, MFS B, and MFS C. The reported r 2 values were calculated for each the dataset including droplets and microparticles data.

Journal: Scientific Reports

Article Title: Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

doi: 10.1038/s41598-020-76477-5

Figure Lengend Snippet: Correlation between observed and predicted droplet/particle sizes with the corresponding r 2 values obtained from the developed ANN-ABC model implemented by Statistica v13.3. Correlations are shown for the training, test, validation and, external datasets for three types of microfluidic systems: MFS A, MFS B, and MFS C. The reported r 2 values were calculated for each the dataset including droplets and microparticles data.

Article Snippet: These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged.

Techniques: Biomarker Discovery