Related papers: Infant Mortality Prediction using Birth Certificat…

The researchers have drawn much attention about the birth weight of newborn babies in the last three decades. The birth weight is one of the vital roles in the babys health. So many researchers such as (2),(1) and (4) analyzed the birth…

Estimates of the under-five mortality rate (U5MR) are used to track progress in reducing child mortality and to evaluate countries' performance related to Millennium Development Goal 4. However, for the great majority of developing…

Biologically, for any organism life does not start at birth but at fertilization of the embryo. Embryonic development is of great importance because it determines congenital anomalies and influences their severity. Whereas there is detailed…

This study aims to understand the factors that resulted in under-five children's malnutrition from the Multiple Indicator Cluster (MICS-2019) nationwide surveys and classify different malnutrition stages based on the four well-established…

The COVID-19 pandemic has had a considerable impact on day-to-day life. Tackling the disease by providing the necessary resources to the affected is of paramount importance. However, estimation of the required resources is not a trivial…

During an epidemic outbreak of a new disease, the probability of dying once infected is considered an important though difficult task to be computed. Since it is very hard to know the true number of infected people, the focus is placed on…

The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its…

The standard methods to calculate the Total Fertility Rate require the reliable age-specific fertility rate including birth data and the related age-specific women's population data. Historically, the number of births was often not counted…

In this article, we use multilevel multinomial logistic regression model to identify the risk factors of anemia in children of northeastern States of India. The data consisted of 10,136 children of age group 6-59 months. We considered the…

To date, developing a good model for early intensive care unit (ICU) mortality prediction is still challenging. This paper presents a patient based predictive modeling framework (PPMF) to improve the performance of ICU mortality prediction…

Existing metrics in competing risks survival analysis such as concordance and accuracy do not evaluate a model's ability to jointly predict the event type and the event time. To address these limitations, we propose a new metric, which we…

The face is a rich source of information that can be utilized to infer a person's biological age, sex, phenotype, genetic defects, and health status. All of these factors are relevant for predicting an individual's remaining lifespan. In…

The majority of biomedical studies use limited datasets that may not generalize over large heterogeneous datasets that have been collected over several decades. The current paper develops and validates several multimodal models that can…

An SEIRS epidemic with disease fatalities is introduced in a growing population (modelled as a super-critical linear birth and death process). The study of the initial phase of the epidemic is stochastic, while the analysis of the major…

The study considers the model of an abstract organism, called Arbitrary Oscillator (ArbO), which is capable of making decisions at each timed step. These decisions are 'critical' since, randomly, their outcome can be 'fatal' for ArbO, thus…

The existing life table method needs to calculate the age-specific mortality first, not only has too many and complicated calculation steps, but also introduces the multiple approximation to bring error. This paper redefines the probability…

Given the limited pool of donor organs, accurate predictions of survival on the wait list and post transplantation are crucial for cardiac transplantation decisions and policy. However, current clinical risk scores do not yield accurate…

We propose a Multi-vAlue Rule Set (MRS) model for in-hospital predicting patient mortality. Compared to rule sets built from single-valued rules, MRS adopts a more generalized form of association rules that allows multiple values in a…

Myocardial Infarction is a main cause of mortality globally, and accurate risk prediction is crucial for improving patient outcomes. Machine Learning techniques have shown promise in identifying high-risk patients and predicting outcomes.…

Since the 1940s, population projections have in most cases been produced using the deterministic cohort component method. However, in 2015, for the first time, in a major advance, the United Nations issued official probabilistic population…