Cardiovascular disease (CVD) is a life-threatening rising considerably in the world. Early detection and prediction of CVD as well other heart diseases might protect many lives. This requires tact clinical data analysis. The potential predictive machine learning algorithms to develop doctor’s perception essential all stakeholders health sector since it can augment efforts doctors have healthier climate for patient diagnosis treatment. We used (ML) algorithm carry out significant explanation...

Abstract Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, its incidence prevalence are increasing in many countries. Modeling CVD plays crucial role understanding the trend cases, evaluating effectiveness interventions, predicting future trends. This study aims to investigate modeling forecasting mortality, specifically Sindh province Pakistan. The civil hospital Nawabshah area province, Pakistan, provided data set used this study. It time series dataset...

<p>This study discusses a novel family of unbiased ratio estimators using the Hartley-Ross (HR) method. The are designed to estimate population distribution function (PDF) in context simple random sampling with non-response. To assess their performance, expressions for variance obtained up initial (first) approximation order. efficiency proposed is evaluated analytically and numerically compared existing estimators. In addition, accuracy assessed four real-world datasets simulation...

The rising of new cases and death counts from the mpox virus (MPV) is alarming. In order to mitigate impact MPV it essential have information virus's future position using more precise time series stochastic models. this present study, a hybrid forecasting system has been developed for infection world daily cumulative confirmed series.

Over the past few decades, utilization of Artificial Intelligence (AI) has surged in popularity, and its application medical field is witnessing a global increase. Nevertheless, implementation AI-based healthcare solutions been slow developing nations like Pakistan. This unique study aims to assess opinion clinical specialists on future replacement AI, associated benefits, drawbacks form southern region

Monkeypox virus is gaining attention due to its severity and spread among people. This study sheds light on the modeling forecasting of new monkeypox cases. Knowledge about future situation using a more accurate time series stochastic models required for actions plans cope with challenge.We conduct side-by-side comparison machine learning approach traditional model. The multilayer perceptron model (MLP), technique, Box-Jenkins methodology, also known as ARIMA model, are used classical...

Population distribution function is a particular area in sample surveys, and several researchers have worked to improve the accuracy of this study by using auxiliary data. Recent studies estimate population applying stratified random sampling non-response techniques, but there are some limitations However, we study, which aims maximize estimating under combined effect groups. To achieve goal condition both introduce use variable two variables (mean ranks). We conduct various estimations for...

Pakistan is considered among the top five countries with highest CO2 emissions globally. This calls for pragmatic policy implementation by all stakeholders to bring finality this alarming situation since it contributes greatly global warming, thereby leading climate change. study an attempt make a comparative analysis of linear time series models nonlinear emission data in Pakistan. These and were used model forecast future values short period. To assess select best these models, we root...

Bitcoin (BTC-USD) is a virtual currency that has grown in popularity after its inception 2008. BTC-USD an internet communication network makes using digital money, including payments, easy. It offers decentralized clearing of transactions and money supply. This study attempts to accurately anticipate the prices (Close) data from September 2023 2024, comprising 390 observations. Four machine learning models—Multi-layer Perceptron, Extreme Learning Machine, Neural Network AutoRegression,...

Forecasting is an attractive topic in every field of study because no one knows the exact nature underlying phenomena, but it can be guessed using mathematical functions. As world progresses towards technology and betterment, algorithms are updated to understand ongoing phenomena. Machine learning (ML) phenomenon used task aspect. Real exchange rate data assumed significant components business market, which plays a pivotal role market trends. In this work, machine models, i.e., Multi-layer...

Carbon dioxide (CO2) emissions have become a critical aspect of the economic and sustainable development indicators every country. In Pakistan, where there is substantial increase in population, industrialization, demand for electricity production from different resources, fear an CO2 cannot be ignored. This study explores link that betwixt with significant Pakistan 1960 to 2018 using autoregressive distributed lag (ARDL) modelling technique. We implemented covariance proportion, coefficient...

Particulate matter with a diameter of 2.5 microns or less ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"><mml:msub><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow><mml:mrow><mml:mn>2.5</mml:mn></mml:mrow></mml:msub></mml:math> ) is significant type air pollution that affects human health due to its ability persist in the atmosphere and penetrate respiratory system. Accurate forecasting particulate crucial for healthcare sector any country. To achieve this, current work, new...

Background. In economic theory, a steady consumer price index (CPI) and its associated low inflation rate (IR) are very much preferred to volatile one. CPI is considered major variable in measuring the IR of country. These indices those changes have significance monetary policy decisions. this study, different conventional machine learning methodologies been applied model forecast Pakistan. Methods. Pakistan’s yearly data from 1960 2021 were modelled using seasonal autoregressive moving...

The use of birth control methods is influenced by complex and competing socioeconomic demographic factors. Regardless the complexity behavioral approach women, utility contraceptive in providing opportunity choice well paired. This study examined factors driving usage contraception impact practices on population growth Pakistan. We also perused quantification sociocultural use.

COVID-19 continues to pose a dangerous global health threat, as cases grow rapidly and deaths increase day by day. This increasing phenomenon does not only affect economic policy but also international around the world. In this paper, Pakistan daily death of COVID-19, from February 25, 2020, March 23, 2022, have been modeled using long-established autoregressive-integrated moving average (ARIMA) model machine learning multilayer perceptron (MLP) model. The most befitting is selected based on...

Export trade is a pivotal driver of economic growth and stability in any nation, including Pakistan. Accurate modelling export holds immense significance as it allows for informed decision-making strategic planning. By employing advanced techniques like machine learning alongside traditional time series models, we can gain deeper insights into the dynamics exports, anticipate trends, adapt policies strategies accordingly. This study focuses on comparative different models forecasting exports...