A Study on Survival Analysis Methods Using Neural Network to Prevent Cancers.

Cancer is one of the main global health threats. Early personalized prediction of cancer incidence is crucial for the population at risk. This study introduces a novel cancer prediction model based on modern recurrent survival deep learning algorithms.

10-year follow-up study on medical expenses and medical care use according to biological age: National Health Insurance Service Health Screening Cohort (NHIS-HealS 2002~2019).

Objectives: The world is witnessing a sharp increase in its elderly population, accelerated by longer life expectancy and lower birth rates, which in turn imposes enormous medical burden on society. Although numerous studies have predicted medical expenses based on region, gender, and chronological age (CA), any attempt has rarely been made to utilize biological age (BA)-an indicator of health and aging-to ascertain and predict factors related to medical expenses and medical care use. Thus, this study employs BA to predict factors that affect medical expenses and medical care use.

Effects of Customized Digital Health Care Service on Metabolic Syndrome Status and Lifestyle Using a Health Care App: Clinical Trial.

Background: Untact cultures have rapidly spread around the world as a result of the prolongation of the COVID-19 pandemic, leading to various types of research and technological developments in the fields of medicine and health care, where digital health care refers to health care services provided in a digital environment. Previous studies relating to digital health care demonstrated its effectiveness in managing chronic diseases such as hypertension and diabetes. While many studies have applied digital health care to various diseases, daily health care is needed for healthy individuals before they are diagnosed with a disease.

Predicting the incidence of age-related diseases based on biological age: The 11-year national health examination data follow-up.

Purpose: As the population ages rapidly, the incidence of age-related diseases (ARDs) is also increasing fast. Predicting the incidence of ARDs is a challenge since the rates of individual aging vary, and objective assessments of the stages of aging based on chronological age (CA) may be inaccurate. Thus, in this study, we developed a biological age (BA) model based on the National Health Examination (NHE) data and analyzed the model prediction results for the incidence of 16 ARDs.

Biological age and lifestyle in the diagnosis of metabolic syndrome: the NHIS health screening data, 2014-2015.

Metabolic syndrome (MS) is diagnosed using absolute criteria that do not consider age and sex, but most studies have shown that the prevalence of MS increases with age in both sexes. Thus, the evaluation of MS should consider sex and age. We aimed to develop a new index that considers the age and sex for evaluating an individual's relative overall MS status.

Biological age as a health index for mortality and major age-related disease incidence in Koreans: National Health Insurance Service - Health screening 11-year follow-up study.

Purpose: A comprehensive health index is needed to measure an individual's overall health and aging status and predict the risk of death and age-related disease incidence, and evaluate the effect of a health management program. The purpose of this study is to demonstrate the validity of estimated biological age (BA) in relation to all-cause mortality and age-related disease incidence based on National Sample Cohort database.

Patients And Methods: This study was based on National Sample Cohort database of the National Health Insurance Service - Eligibility database and the National Health Insurance Service - Medical and Health Examination database of the year 2002 through 2013.

Models for estimating the metabolic syndrome biological age as the new index for evaluation and management of metabolic syndrome.

Purpose: This study aims to propose a metabolic syndrome (MS) biological age model, through which overall evaluation and management of the health status and aging state in MS can be done easily. Through this model, we hope to provide a novel evaluation and management health index that can be utilized in various health care fields.

Patient And Methods: MS parameters from American Heart Association/National Heart, Lung, and Blood Institute guidelines in 2005 were used as biomarkers for the estimation of MS biological age.

Models for estimating the biological age of five organs using clinical biomarkers that are commonly measured in clinical practice settings.

Objectives: To date, no worldwide studies have been conducted to estimate the biological age of five organs using clinical biomarkers that are associated with the aging status. Therefore, we conducted this study to develop the models for estimating the biological age of five organs (heart, lung, liver, pancreas, and kidney) using clinical biomarkers which are commonly measured in clinical practice.

Design: A cross sectional study.

A model for estimating body shape biological age based on clinical parameters associated with body composition.

Background: To date, no studies have attempted to estimate body shape biological age using clinical parameters associated with body composition for the purposes of examining a person's body shape based on their age.

Objective: We examined the relations between clinical parameters associated with body composition and chronological age, and proposed a model for estimating the body shape biological age.

Methods: The study was conducted in 243,778 subjects aged between 20 and 90 years who received a general medical checkup at health promotion centers at university and community hospitals in Korea from 2004 to 2011.

Development of models for predicting biological age (BA) with physical, biochemical, and hormonal parameters.

Individual differences are the hallmark of aging. Chronological age (CHA) is known that fails to provide an accurate indicator of the aging but biological age (BA) estimates the functional status of an individual in reference to his or her chronological peers on the basis of how well he or she functions in comparison with others of the same CHA. Therefore, we developed models for predicting BA that can be applicable in clinical practice settings.

Hypocholesterolemic property of Yucca schidigera and Quillaja saponaria extracts in human body.

This study was undertaken to observe the effects of the blend of partially purified Yucca schidigera and Quillaja saponaria extracts on cholesterol levels in the human's blood and gastrointestinal functions, and to determine if a new cholesterol-lowering drug can be developed by the further purification of the extracts. Ultrafiltration and sequential diafiltration increased the amounts of steroidal saponin in aqueous yucca extract and terpenoid saponin in aqueous quillaja extract from 9.3% and 21.