相关论文: Automatic end-to-end De-identification: Is high ac…
The robust development of Electronic Health Records (EHRs) causes a significant growth in sharing EHRs for clinical research. However, such a sharing makes it difficult to protect patient's privacy. A number of automated de-identification…
Patient notes contain a wealth of information of potentially great interest to medical investigators. However, to protect patients' privacy, Protected Health Information (PHI) must be removed from the patient notes before they can be…
Electronic Health Records (EHRs) have become the primary form of medical data-keeping across the United States. Federal law restricts the sharing of any EHR data that contains protected health information (PHI). De-identification, the…
Objective: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can only access de-identified notes, in order to protect the…
Background: Electronic health records (EHRs) are a valuable resource for data-driven medical research. However, the presence of protected health information (PHI) makes EHRs unsuitable to be shared for research purposes. De-identification,…
De-identification is the task of detecting protected health information (PHI) in medical text. It is a critical step in sanitizing electronic health records (EHRs) to be shared for research. Automatic de-identification classifierscan…
Electronic Health Records (EHR) are crucial for the success of digital healthcare, with a focus on putting consumers at the center of this transformation. However, the digitalization of healthcare records brings along security and privacy…
Background: More than half (57%) of pharma clinical research spend is in support of clinical trials. One reason is that Electronic Health Record (EHR) systems and HIPAA privacy rules often limit how broadly patient information can be…
An Electronic Health Record (EHR) system must enable efficient availability of meaningful, accurate and complete data to assist improved clinical administration through the development, implementation and optimisation of clinical pathways.…
In the era of big data, there is an increasing need for healthcare providers, communities, and researchers to share data and collaborate to improve health outcomes, generate valuable insights, and advance research. The Health Insurance…
Electronic Health Records (EHRs) are pivotal in clinical practices, yet their retrieval remains a challenge mainly due to semantic gap issues. Recent advancements in dense retrieval offer promising solutions but existing models, both…
The electronic health record (EHR) targets the systematized collection of patient-specific electronically-stored health data. Currently the EHR is an evolving concept driven by ongoing technical developments and open or unclear legal issues…
The introduction of electronic personal health records (EHR) enables nationwide information exchange and curation among different health care systems. However, the current EHR systems do not provide transparent means for diagnosis support,…
De-identification of medical images is a critical step to ensure privacy during data sharing in research and clinical settings. The initial step in this process involves detecting Protected Health Information (PHI), which can be found in…
Use of medical data, also known as electronic health records, in research helps develop and advance medical science. However, protecting patient confidentiality and identity while using medical data for analysis is crucial. Medical data can…
Medical data employed in research frequently comprises sensitive patient health information (PHI), which is subject to rigorous legal frameworks such as the General Data Protection Regulation (GDPR) or the Health Insurance Portability and…
In present technological era, healthcare providers generate huge amount of clinical data on daily basis. Generated clinical data is stored digitally in the form of Electronic Health Records (EHR) as a central data repository of hospitals.…
Timely sharing of electronic health records (EHR) across providers is essential and significance in facilitating medical researches and prompt patients' care. With sharing, it is crucial that patients can control who can access their data…
Medical entity extraction (EE) is a standard procedure used as a first stage in medical texts processing. Usually Medical EE is a two-step process: named entity recognition (NER) and named entity normalization (NEN). We propose a novel…
Electronic health records (EHRs) and other real-world clinical data are essential for clinical research, medical artificial intelligence, and life science, but their sharing is severely limited by privacy, governance, and interoperability…