The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a method to address this problem using Deep Learning and Electronic Health Record...
Cataract is a cloudiness of eye lens and studies have reported many risk factors for the development of cataract. However, the cumulative effect of multiple factors along with clinical and systemic disease conditions have not been adequately tested due to a limitation in methodology. The collection of a large volume of Electronic Health Records (EHR) offers an opportunity to apply computational tools...
With the rapid development of hospital information technologies, more and more hospitals build electronic medical record (EMR) systems, which provides a comprehensive source for medical data mining and analysis. Most current EMR systems adopt a mixed structure. On the other hand, most data mining algorithms are designed for highly structured data. In this paper, we study the problem of interesting...
Clinical research registries need to be driven by data quality to improve the outcome of clinical trials and to provide the possibility to facilitate new research initiatives. The International Niemann-Pick Disease Registry (INPDR) is one such example of a clinical research registry. Unlike other registries where data quality is largely based around best effort manual data entry, the INPDR registry...
This paper describes a principled statistical methodof preprocessing incidentally collected electronic medical recordsto facilitate short-term predictions of disease onset withoutexplicit interaction with patients (e.g., medical tests, questionnaires). The model is also applicable to detection of remission. In incidentally collected data, records are possibly left and righttruncated - the first time...
The purpose of using Predictive Modeling for presumptive diagnosis of Type 2 Diabetes Mellitus based on symptomatic analysis is the optimization of the diagnosis phase of the disease through the process of evaluating symptomatic characteristics and daily habits, allowing the forecasting of T2DM without the need of medical exams through predictive analysis. The tool used was SAP Predictive Analytics...
Clinical examination of the patient with suspected stroke to determine the type of pathology is still widely applied, especially in Indonesia due to constraints in the implementation of the Gold Standard Procedure. Clinically, the examination of the various features starts from the physical symptoms, medical history and laboratory results, which might take long duration and costly. Moreover, not all...
Respiratory tract infections are one of the major complaints in preschool children. The aim of this study was to highlight the particularities of recurrent respiratory tract infections manifested by ETN and pulmonary infections in children. Materials and methods: The authors performed a retrospective study of 148 patients aged between 2 months and 5 years old, hospitalized with the recurrent respiratory...
This paper studies the feasibility of privacy-preservingdata mining in epidemiological study. As for the data-miningalgorithm, we focus to a linear multiple regression thatcan be used to identify the most significant factorsamong many possible variables, such as the historyof many diseases. We try to identify the linear model to estimate a lengthof hospital stay from distributed dataset related tothe...
It is a critical issue to predict the prognosis of adult disease patients due to the possibility of spreading to high-risk symptoms in medical fields. Most studies for predicting prognosis have used complex data from patients such as biomedical images, biomarkers, and pathological measurements. We demonstrate a language model-like method for predicting high-risk prognosis from diagnosis histories...
The increasing trend of systematic collection of medical data (diagnoses, hospital admission emergencies, blood test results, scans etc) by health care providers offers an unprecedented opportunity for the application of modern data mining, pattern recognition, and machine learning algorithms. The ultimate aim is invariably that of improving outcomes, be it directly or indirectly. Notwithstanding...
In this fast moving world, people are ignorant about their health issues and avoid routine check-ups. It is very difficult for users to spend longer time on-line and explore health information. To solve this problem, we provide voice-based android application to the user where user can interact with system and get inference of diseases and their remedies by giving the symptoms as input. For processing...
We developed a simple approach to predict risk of developing Ischemic Heart Disease (IHD) (Heart Attack) using smartphone. An Android based prototype software has been developed by integrating clinical data obtained from patients admitted with IHD. The clinical data from 787 patients has been analyzed and correlated with the risk factors like Hypertension, Diabetes, Dyslipidemia (Abnormal cholesterol),...
This paper proposes a method which induces a clinical pathway by using sample and attribute clustering of the histories of nursing orders stored in hospital information system. The method consists of the following five steps: first, frequencies of nursing orders are extracted from hospital information system. Second, orders are classified into several groups by using sample clustering. Then, attributes...
Decisions must be made regarding screening and treatment strategies under budget constraints for chronic hepatitis C birth-cohorts in the U.S. A Markov model of disease progression is able to evaluate health utility gain using quality-adjusted life years (QALYs) for each strategy. Through conducting a simulation optimization algorithm, Probabilistic Branch and Bound (PBnB), we not only provide an...
The emergence of electronic health records (EHRs) has made medical history including past and current diseases, and prescribed medications easily available. This has facilitated development of personalized and population health care management systems. Contemporary disease prediction systems leverage data such as disease diagnoses codes to compute patients' similarity and predict the possible future...
Medication error in the treatment process can be dangerous for patients that can cause adverse medicine reactions. This can occur because of allergies, medicine-medicine interactions, medicine interactions with diseases and medicine incompatibility which include duration of therapy, dose, route of administration, and amount of medicine. That is way it takes knowledge and thoroughness doctors in selecting...
The background of the research is to analyze data derived from an elucidation of catfish and carp diseases in Kediri, East Java, Indonesia. The research shows that data about fish's disease history have not been used effectively because it is only be collected. Data about fish's symptom history used by fish trainer only present the number of fish that get disease. Data about fish's history should...
Computer based analysis of Electronic Health Records (EHRs) has the potential to provide major novel insights of benefit both to specific individuals in the context of personalized medicine, as well as on the level of population-wide health care and policy. The present paper introduces a novel algorithm that uses machine learning for the discovery of longitudinal patterns in the diagnoses of diseases...
Chronic Obstructive Pulmonary Disease (COPD) and asthma each represent a large proportion of the global disease burden; COPD is the third leading cause of death worldwide and asthma is one of the most prevalent chronic diseases, afflicting over 300 million people. Much of this burden is concentrated in the developing world, where patients lack access to physicians trained in the diagnosis of pulmonary...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.