API Documentation

Jain, Jagdeep

doi:10.1007/978-1-4842-8142-0_11

Cited by 6 publications

(4 citation statements)

References 17 publications

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“…The former is a surface on which one can draw using DrawingContext class. This class contains Draw-Line method suitable for the purpose of signal plotting [6]. This method is simple from the developer point of view, however, fl exibility is lower comparing to WriteableBitmap.…”

Section: Drawingvisual Methodsmentioning

confidence: 99%

Real-Time Plotting of Biomedical Signals in Applications Utilizing Windows Presentation Foundation Technology

Sobotnicka¹,

Feige²

2023

PJAMBP

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Utilization of personal computers in medicine requires strong emphasis on software performance. Contemporary programming languages give engineers great flexibility in developing applications. Since these technologies are more and more complex, there is a need to analyze methods of achieving desired results taking into account time requirements. This paper focuses mainly on development of plotting module using Windows Presentation Foundation library, which is one of the newest tool for software developers. Aspects of plotter creation for technologically limited screen are covered and conclusions are summarized giving recommendations regarding the topic. General methods of drawing signal on a raster surface are also discussed. Since medical signals in monitoring range consist of frequencies up to about 100 Hz, one has to take into account aspects of signal scaling in order to not to make its important parts invisible. The main problem is that personal computer screen, e.g. a monitor, is purely digital in nature; actually it is the set of pixels (consisting of three components). Because resolution is limited, the signal must be limited in frequency to the range which can be shown at a given plotting speed. This paper describes these aspects of signal plotting as well as the method for virtually increasing pixel resolution by using particular components of a pixel. This paper is a summary giving a general idea of the capabilities of the above mentioned WPF technology and the basis for creating such programs using methods such as: WriteableBitmap method, DrawingVisual method, Canvas Method type 1, Canvas Method type 2.

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Section: Drawingvisual Methodsmentioning

confidence: 99%

Real-Time Plotting of Biomedical Signals in Applications Utilizing Windows Presentation Foundation Technology

Sobotnicka¹,

Feige²

2023

PJAMBP

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“…The NHS platform provides an application programming interface (API) that allows access to the patient ratings and reviews [20]. A custom web scraper was built for the project using the NHS API to collect the patient ratings and reviews.…”

Section: Nhs Patient Feedbackmentioning

confidence: 99%

Automating Large-scale Health Care Service Feedback Analysis: Sentiment Analysis and Topic Modeling Study (Preprint)

Alexander¹,

Bahja²,

Butt³

2021

Preprint

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UNSTRUCTURED Obtaining patient feedback is an essential mechanism for healthcare service providers to assess their quality and effectiveness. Unlike assessments of clinical outcomes, feedback from patients offers insights into their lived experience. The Department of Health and Social Care in England via NHS Digital operates a patient feedback web service through which patients can leave feedback of their experiences into structured and free-text report forms. Free-text feedback compared to structured questionnaires may be less biased by the feedback collector thus more representative; however, it is harder to analyse in large quantities and challenging to derive meaningful, quantitative outcomes for better representation of the general public feedback. This study details the development of a text analysis tool that utilises contemporary natural language processing (NLP) and machine learning models to analyse free-text clinical service reviews to develop a robust classification model, and interactive visualisation web application based on a Vue.js application with NodeJS, working with a C# serverless API and SQL server all hosted on Microsoft Azure Platform, which facilitates exploration of the data, designed for the use by all stakeholders. Of the 11,103 possible clinical services that could be reviewed across England, 2030 different services had received a combined total of 51,845 reviews between 1/10/2017 and 31/10/2019; these were included for analysis. Dominant topics were identified for the entire corpus and then negative and positive sentiment topics in turn. Reviews containing high and low sentiment topics occurred more frequently than less polarised topics. Time series analysis can identify trends in topic and sentiment occurrence frequency across the study period. This tool automates the analysis of large volumes of free text specific to medical services, and the web application summarises the results and presents them in an accessible and interactive format. Such a tool has the potential to considerably reduce administrative burden and increase user uptake.

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“…We have found that HC1 and HC2 both are using Light Gradient Boost (LGB) model for prediction. The code for building the two models are: inversely proportional to the frequency of the class [25,43]. In this case, HC1 mitigates the male-female imbalance in its prediction.…”

Section: Analyze Fairness Of the Modelsmentioning

confidence: 99%

“…We have observed that class_weight hyperparameter in LGBMClassifier allows developers to control group fairness directly. However, the library documentation of LGB classifier suggests that this parameter is used for improving performance of the models [43,47]. Though the library documentation mentions about probability calibration of classes to boost the prediction performance using this parameter, however, there is no suggestion regarding the effect on the bias introduced due to the wrong choice of this parameter.…”

Section: Analyze Fairness Of the Modelsmentioning

confidence: 99%

Understanding unfairness and its mitigation in open-source machine learning models

Biswas

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API Documentation

Cited by 6 publications

References 17 publications

Real-Time Plotting of Biomedical Signals in Applications Utilizing Windows Presentation Foundation Technology

Real-Time Plotting of Biomedical Signals in Applications Utilizing Windows Presentation Foundation Technology

Automating Large-scale Health Care Service Feedback Analysis: Sentiment Analysis and Topic Modeling Study (Preprint)

Understanding unfairness and its mitigation in open-source machine learning models

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