Design and Implementation of Advanced Machine Learning Management and Its Impact on Better Healthcare Services: A Multiple Regression Analysis Approach (MRAA)

Abstract

In the current information and technology era, business enterprises are focusing in performing the process effectively by reducing the waiting time in completing the work, reduce latency and deploy the resources effectively so as to service the patient, medical practitioners, societies, and other stakeholders in an efficient manner. Hence, several organisations are using the emerging technologies so as to obtain high performance and enhance competitive edge. The advancement in machine learning, deep learning, business analytics, etc. enables the health care industry to identify the patterns based on the data collected and create a pivotal position and enhance revenues and profits in a sustainable manner. Machine learning models are considered as computational algorithms which will enable in collected the data, analyze them, and provide the necessary reports to the experts and management in order to make informed decision making. The application of advanced machine learning enables the organisation to process the image effectively, recognize the voice and enable in servicing the customers, process the available data, and identify the patterns so as to make informed decision making. The basic purpose of the study is to analyze the overall implementation of advanced machine learning approaches towards health care services for providing enhanced services, better patient engagement, and support in creating better life for them, the researchers intend to collect the closed-ended questionnaire from employees in different medical centers covering: apprehend the nature of designing and implementation of machine learning approaches in the organisation and understand the effectiveness of these tools in enhancing the sustainable growth and development of the organisation.

[Retracted] Research on Injury Causes and Prevention Effect of College Rowing Athletes Based on Multiple Regression and Residual Algorithm

“…The synergistic combination of athletes' injury causes is as follows: collaboration is the main way to realize dynamic analysis in rowing competition. The algorithm in this paper is based on the prevention effect of multiple regression and diagnoses the dynamic distributed cooperative combination form [ 18 ]. Different submultiple regressions use different cooperative combination forms, complex parameters, and operations.…”

“…Prevention and Control Measures and Steps of Athletes' Injury Causes. The basic idea of multiple regression and prevention effect is to use different synergy and combination forms to realize damage cause analysis [18], obtain global optimal measures, and improve the accuracy of measure formulation. The implementation steps of this algorithm are shown in Figure 6.…”

The Climate Changes and the Simulation of the Runoff in the Last 50 years (1961–2010) in the Upper Tarim River Basin of Southern Xinjiang, China

“…One of the commonly used methods is to calculate the runoff data using statistical methods, and the other is to set up a prediction model according to the evolution of the predicted subject. We used statistical methods including linear regression and nonlinear regression, based on the observed data, to predict and analyze the runoff situations [32][33][34][35][36][37][38]. Speaking specifically, based on the monthly runoff data of the upper mountain areas of the Tarim River basin, from the Alar station, during the period of 1961-2010, and precipitation and temperature data in mountainous areas, the influence of the temporal-spatial component of regional precipitation and temperature on monthly runoff was analyzed by using least-squares methods and radial basis function (RBF) neural network.…”

Retracted: Design and Implementation of Advanced Machine Learning Management and Its Impact on Better Healthcare Services: A Multiple Regression Analysis Approach (MRAA)

“…This article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”