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Objective: We sought to test a 3-parameter model for diagnosis of dizziness based on the type and temporal characteristics of the dizziness and on hearing status.
We designed a telemedicine model for diagnosis of common, acute illness to compare telemedicine and in-person evaluations on reproducibility of diagnosis and treatment.
We test our method on Hepar II, a model for diagnosis of liver disorders, whose parameters are extracted from a real, small set of patient records.
The objective of this study was to characterize patient demographics, risk factors, and anatomic distribution of upper extremity deep venous thrombosis (UEDVT) to develop a probability model for diagnosis.
However, one drawback using such a model for diagnosis is that fault isolation often requires that the model, in addition to the fault free case, also describes the faulty system, and thereby measurements of the faulty system are needed, which is costly.
Fig. 5 FNC model for diagnosis of diabetes.
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The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset.
This work proposes a KE methodology called Timed Observation Modelling For Diagnosis (TOM4D) which allows building dynamic process models from experts' knowledge and data where the obtained models can be compared and combined with models obtained through a KDD process in order to define a model more suitable to the dynamic process reality.
Using multivariate statistical analysis we could generate powerful models for diagnosis and prognosis of septic shock.
Logistic regression and ANN are currently the most widely used models for diagnosis and prognosis studies in biomedicine.
Different prediction models for diagnosis of (persistent) erosive disease have been described by means of different ACPA assays [ 22, 23].
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com