相关论文: Electronic Health Records and Cloud based Generic …
Synthetic health data have the potential to mitigate privacy concerns when sharing data to support biomedical research and the development of innovative healthcare applications. Modern approaches for data generation based on machine…
There is a growing demand for the use of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, particularly as clinical decision support systems to assist medical professionals. However, the complexity of many of these…
Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based solutions for EMR analysis concentrate on learning the…
The demand of transparency of clinical research results, the need of accelerating the process of transferring innovation in the daily medical practice as well as assuring patient safety and product efficacy make it necessary to extend the…
Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the…
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…
The fundamental aim of the healthcare sector is to incorporate different technologies to observe and keep a track of the various clinical parameters of the patients in day to day life. Distant patient observation applications are becoming…
Electronic health records (EHRs) are rich clinical data sources but complex repositories of patient data, spanning structured elements (demographics, vitals, lab results, codes), unstructured clinical notes and other modalities of data.…
Today cloud computing infrastructure is largely being deployed in healthcare to access various healthcare services easily over the Internet on an as needed basis. The main advantage of healthcare cloud is that it can be used as a tool for…
Electronic Health Records (EHR) are time-series relational databases that record patient interactions and medical events over time, serving as a critical resource for healthcare research and applications. However, privacy concerns and…
This is the preprint version of our paper on JOMS. In this paper, two mHealth applications are introduced, which can be employed as the terminals of bigdata based health service to collect information for electronic medical records (EMRs).…
With recent elevated adaptation of cloud services in almost every major public sector, the health sector emerges as a vulnerable segment, particularly in data exchange of sensitive Health records, as determining the retention, exchange, and…
In-home health monitoring has attracted great attention for the ageing population worldwide. With the abundant user health data accessed by Internet of Things (IoT) devices and recent development in machine learning, smart healthcare has…
Electronic health records (EHR) systems contain vast amounts of medical information about patients. These data can be used to train machine learning models that can predict health status, as well as to help prevent future diseases or…
Substantial increase in the use of Electronic Health Records (EHRs) has opened new frontiers for predictive healthcare. However, while EHR systems are nearly ubiquitous, they lack a unified code system for representing medical concepts.…
While randomized controlled trials (RCTs) are the gold-standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world data (RWD) has been vital in post-approval monitoring and…
Background: The integration of the General Data Protection Regulation (GDPR) and the Medical Device Regulation (MDR) creates complexities in conducting Data Protection Impact Assessments (DPIAs) for medical devices. The adoption of…
Electronic health records (EHRs) contain vast amounts of complex data, but harmonizing and processing this information remains a challenging and costly task requiring significant clinical expertise. While large language models (LLMs) have…
This study describes the creation of a wireless, transportable Holter monitor to improve the accuracy of cardiac disease diagnosis. The main goal of this study is to develop a low-cost cardiac screening system suited explicitly for…
Electronic health records (EHR) contain extensive structured and unstructured data, including tabular information and free-text clinical notes. Querying relevant patient information often requires complex database operations, increasing the…