Graphs are very effective tools in visualizing information and are used in many fields including the medical field. In most developing countries primary care, graphs are used to monitor child growth. These measures are therefore often displayed using line graphs, basing it on three indicators (stunting, underweight and wasting) based on the WHO 2006 Child Growth Standard. Most literature on information visualization of electronic health record data focuses on aggregate data visualization tools. This research therefore, was set out to provide such an overview of requirements for computerized graphs for individual patient data, implemented in a way that all kinds of medical graphs showing the development of medical measures over time can be displayed. This research was interpretive, using a user-centric approach for data collection where interviews and web search was used to ensure that the graphs developed are fit the user requirements. This followed prototype development using one of the three free, open source software libraries for Android that were evaluated. The prototype was then used to refine the user requirements. The health workers interpreted the graphs developed flawlessly.
America has one of the best medical systems in the world. The medical treatment care options offered by the medical system make it sophisticated. However, many American patients are not receiving health care on a regular basis, and at the same time, they cannot afford it. Also, the current medical system has many flaws such as high medical treatment costs and lack of doctors to accommodate many patients. This paper presents the principles of medical artificial intelligence called the knowledge based system. Doctors can remotely check and monitor their patients health data, medical history, how…
In this paper, we report an extensive analysis that we performed in two scenarios where the care relation between doctor and patients are mediated by the relatives of the patients: Pediatric Palliative Care (PPC) and Nursing Homes (NH). When the patients are children or very old adults in the end of life, the provision of care often involve a family caregiver as the main point of contact for the health service. PPC and NH are characterized by emotional complexity, since incurable diseases expose the family caregivers to heavy careload and human distress. In this paper, we discuss our findings …
Electronic Health Records (EHRs) contain a large volume of heterogeneous patient data, which are useful at the point of care and for retrospective research. These data are typically stored in relational databases. Gaining an integrated view of these data for a single patient typically requires complex SQL queries joining multiple tables. In this work, we present a visualization tool that integrates heterogeneous health care data (e.g., clinical notes, laboratory test values, vital signs) into a single timeline. We train risk models offline and dynamically generate and present their predictions…
Managing health-care records and information is an imperative necessity. Most patient health records are stored in separate systems and there are still huge paper trails of records that health-care providers must keep to comply with different regulations. This paper proposes an RFID-based system, named SIMOPAC, that integrate RFID technology in health care in order to make patient emergency care as efficient and risk-free as possible, by providing doctors with as much information about a patient as quickly as possible. Every hospital could use SIMOPAC with their existing system in order to pro…
OBJECTIVE: To test the hypothesis that variation in care coordination is related to LOS. DESIGN We applied a spectral co-clustering methodology to simultaneously infer groups of patients and care coordination patterns, in the form of interaction networks of health care professionals, from electronic medical record (EMR) utilization data. The care coordination pattern for each patient group was represented by standard social network characteristics and its relationship with hospital LOS was assessed via a negative binomial regression with a 95% confidence interval. SETTING AND PATIENTS This stu…
When most patients visit physicians in a clinic or a hospital, they are asked about their medical history and related medical tests' results which might not exist or might simply have been lost over time. In emergency situations, many patients suffer or sadly die because of lack of pertinent medical information. Patient's Health information (PHI) saved by Electronic Medical Record (EMR) could be accessible only by a hospital using their EMR system. Furthermore, Personal Health Record (PHR) information cannot be solely relied on since it is controlled solely by patients. This paper introduces a…
Social Media has been transforming numerous activities of everyday life, impacting also healthcare. However, few studies investigate the medical use of social media by patients and medical practitioners, especially in the Arabian Gulf region and Kuwait. To understand the behavior of patients and medical practitioners in social media toward healthcare and medical purposes, we conducted user studies. Through an online survey, we identified a decrease in patients and medical practitioners use of social media for medical purposes. Patients reported to be more aware than practitioners concerning: h…
Electronic medical records (EMR) contain sensitive personal information. For example, they may include details about infectious diseases, such as human immunodeficiency virus (HIV), or they may contain information about a mental illness. They may also contain other sensitive information such as medical details related to fertility treatments. Because EMRs are subject to confidentiality requirements, accessing and analyzing EMR databases is a privilege given to only a small number of individuals. Individuals who work at institutions that do not have access to EMR systems have no opportunity to …
Medical images require immediate access by several physicians in different places within a medical facility and access to a critically injured persons medical image, such as the x-ray, on time can be a key factor in the diagnosis and treatment of the patient. The electronic medical image archive system can help to solve the problem faced in previous physical medium archiving, thus increasing productivity and time which patients are attended to. In this paper, simple but functional electronic medical image archive architecture was proposed and implemented. The system was further evaluated in a …
The transfer of the medical care services to the patient, rather than the transport of the patient to the medical services providers is aim of the project. This is achieved by using web-based applications including Modern Medical Informatics Services which is easier, faster and less expensive. The required system implements the suitable informatics and electronics solutions efficiently for the Tele-medicine care. We proposed an approach to manage different multimedia medical databases in the telemedicine system. In order to be efficiently and effectively manage, search, and display database in…
The outpatients department in a developing country is typically understaffed and inadequately equipped to handle a large numbers of patients filing through on an average day. The use of electronic medical record (EMR) systems can resolve some of the longstanding medical inefficiencies common in developing countries. This paper presents the design and implementation of a proposed outpatient management system that enables efficient management of a patient's medical details. We present a system to create appointments with medical practitioners by integrating a proposed Android-based mobile applic…
Readmission rates in the hospitals are increasingly being used as a benchmark to determine the quality of healthcare delivery to hospitalized patients. Around three-fourths of all hospital re-admissions can be avoided, saving billions of dollars. Many hospitals have now deployed electronic health record (EHR) systems that can be used to study issues that trigger readmission. However, most of the EHRs are high dimen-sional and sparsely populated, and analyzing such data sets is a Big Data challenge. The effect of some of the well-known dimension reduction techniques is minimized due to presence…
There is a clear need to involve patients in medical decisions. However, cognitive psychological research has highlighted the cognitive limitations of humans with respect to 1. Probabilistic assessment of the patient state and of potential outcomes of various decisions, 2. Elicitation of the patient utility function, and 3. Integration of the probabilistic knowledge and of patient preferences to determine the optimal strategy. Therefore, without adequate computational support, current shared decision models have severe ethical deficiencies. An informed consent model unfairly transfers the resp…
Institute of Hospital and Health Care Administration（医院与健康照护管理研究所）；National Yang Ming Chiao Tung University（国立阳明交通大学）；Far Eastern Memorial Hospital（远东纪念医院）
The global COVID-19 pandemic has caused more than six million deaths worldwide. Medicalized hotels were established in Taiwan as quarantine facilities for COVID-19 patients with no or mild symptoms. Due to limited medical care available at these hotels, it is of paramount importance to identify patients at risk of clinical deterioration. This study aimed to develop and evaluate a graph-based deep learning approach for progressive hospital transfer risk prediction in a medicalized hotel setting. Vital sign measurements were obtained for 632 patients and daily patient similarity graphs were cons…
East China University of Science and Technology（华东理工大学）；School of Information Science and Engineering, East China University of Science and Technology（华东理工大学信息科学与工程学院）；Shanghai Shuguang Hospital（上海曙光医院）
Medical activities, such as diagnoses, medicine treatments, and laboratory tests, as well as temporal relations between these activities are the basic concepts in clinical research. However, existing relational data model on electronic medical records (EMRs) lacks explicit and accurate semantic definitions of these concepts. It leads to the inconvenience of query construction and the inefficiency of query execution where multi-table join queries are frequently required. In this paper, we propose a patient event graph (PatientEG) model to capture the characteristics of EMRs. We respectively def…
Massachusetts Institute of Technology（麻省理工学院）；University of Massachusetts（马萨诸塞大学）；Harvard T.H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院）；Massachusetts General Hospital（麻省总医院）；Tufts University School of Medicine（塔夫茨大学医学院）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；Washington University School of Medicine（华盛顿大学医学院）；Philips Research North America（飞利浦北美研究院）；Harvard University（哈佛大学）；Adobe Research（Adobe研究院）
A crucial step within secondary analysis of electronic health records (EHRs) is to identify the patient cohort under investigation. While EHRs contain medical billing codes that aim to represent the conditions and treatments patients may have, much of the information is only present in the patient notes. Therefore, it is critical to develop robust algorithms to infer patients' conditions and treatments from their written notes. In this paper, we introduce a dataset for patient phenotyping, a task that is defined as the identification of whether a patient has a given medical condition (also ref…
Sepsis is an important cause of mortality, especially in intensive care unit (ICU) patients. Developing novel methods to identify early mortality is critical for improving survival outcomes in sepsis patients. Using the MIMIC-III database, we integrated demographic data, physiological measurements and clinical notes. We built and applied several machine learning models to predict the risk of hospital mortality and 30-day mortality in sepsis patients. From the clinical notes, we generated clinically meaningful word representations and embeddings. Supervised learning classifiers and a deep learn…
For centuries nursing has been known as a job that requires complex manual operations, that cannot be automated or replaced by any machinery. All the devices and techniques have been invented only to support, but never fully replace, a person with knowledge and expert intuition. With the rise of Artificial Intelligence and continuously increasing digital data flow in healthcare, new tools have arrived to improve patient care and reduce the labour-intensive work conditions of a nurse. This cross-disciplinary review aims to build a bridge over the gap between computer science and nursing. It out…
With the development of the Internet of Things(IoT) and Artificial Intelligence(AI) technologies, human activity recognition has enabled various applications, such as smart homes and assisted living. In this paper, we target a new healthcare application of human activity recognition, early mobility recognition for Intensive Care Unit(ICU) patients. Early mobility is essential for ICU patients who suffer from long-time immobilization. Our system includes accelerometer-based data collection from ICU patients and an AI model to recognize patients' early mobility. To improve the model accuracy and…
In the old age, few people need special care if they are suffering from specific diseases as they can get stroke while they are in normal life routine. Also patients of any age, who are not able to walk, need to be taken care of personally but for this, either they have to be in hospital or someone like nurse should be with them for better care. This is costly in terms of money and man power. A person is needed for 24x7 care of these people. To help in this aspect we purposes a vision based system which will take input from the patient and will provide information to the specified person, who …
Objectives To develop and evaluate machine learning models to detect suspected undiagnosed nonalcoholic steatohepatitis (NASH) patients for diagnostic screening and clinical management. Methods In this retrospective observational noninterventional study using administrative medical claims data from 1,463,089 patients, gradient-boosted decision trees were trained to detect likely NASH patients from an at-risk patient population with a history of obesity, type 2 diabetes mellitus (T2DM), metabolic disorder, or nonalcoholic fatty liver (NAFL). Models were trained to detect likely NASH in all at-r…
Retained surgical bodies (RSB) are any foreign bodies left inside the patient after a medical procedure. RSB is often caused by human mistakes or miscommunication between medical staff during the procedure. Infection, medical complications, and even death are possible consequences of RSB, and it is a significant risk for patients, hospitals, and surgical staff. In this paper. we describe the engineering process we have done to explore the design space, define a feasible solution, and simulate, verify, and validate a state-of-the-art Cyber-Physical System that can significantly decrease the inc…
Stanford University（斯坦福大学）；Stanford University School of Medicine（斯坦福大学医学院）
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 (EHR) data, which is currently being piloted, with Institutional Review Board approval, at an academic medical center. The EHR data of admitted patients are automatically evaluated by an algorithm, wh…
Demand for health care is constantly increasing due to the ongoing demographic change, while at the same time health service providers face difficulties in finding skilled personnel. This creates pressure on health care systems around the world, such that the efficient, nationwide provision of primary health care has become one of society's greatest challenges. Due to the complexity of health care systems, unforeseen future events, and a frequent lack of data, analyzing and optimizing the performance of health care systems means tackling a wicked problem. To support this task for primary care,…
CEA, LIST（法国原子能与替代能源委员会信息技术与系统实验室）；Faculté de Médecine Paris-Sud（巴黎南大学医学院）
In medicine, a communicating virtual patient or doctor allows students to train in medical diagnosis and develop skills to conduct a medical consultation. In this paper, we describe a conversational virtual standardized patient system to allow medical students to simulate a diagnosis strategy of an abdominal surgical emergency. We exploited the semantic properties captured by distributed word representations to search for similar questions in the virtual patient dialogue system. We created two dialogue systems that were evaluated on datasets collected during tests with students. The first syst…
