AIMC Topic: Electronic Health Records
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RETRACTED: Diagnosis labeling with disease-specific characteristics mining.
Artificial intelligence in medicine
Jul 31, 2018
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors; serious errors had been introd...
Utilizing Big Data in Cancer Care.
Surgical oncology clinics of North America
Jul 23, 2018
Clinical research has boomed over the past decade, with the development of multiple clinical datasets that are available for retrospective review. However, data remain incomplete based on fragmented reporting, provider change, and loss of follow-up. ...
Discovering and identifying New York heart association classification from electronic health records.
BMC medical informatics and decision making
Jul 23, 2018
BACKGROUND: Cardiac Resynchronization Therapy (CRT) is an established pacing therapy for heart failure patients. The New York Heart Association (NYHA) class is often used as a measure of a patient's response to CRT. Identifying NYHA class for heart f...
Using natural language processing methods to classify use status of dietary supplements in clinical notes.
BMC medical informatics and decision making
Jul 23, 2018
BACKGROUND: Despite widespread use, the safety of dietary supplements is open to doubt due to the fact that they can interact with prescribed medications, leading to dangerous clinical outcomes. Electronic health records (EHRs) provide a potential wa...
Natural Language Processing and Its Implications for the Future of Medication Safety: A Narrative Review of Recent Advances and Challenges.
Pharmacotherapy
Jul 22, 2018
The safety of medication use has been a priority in the United States since the late 1930s. Recently, it has gained prominence due to the increasing amount of data suggesting that a large amount of patient harm is preventable and can be mitigated wit...
Postoperative bleeding risk prediction for patients undergoing colorectal surgery.
Surgery
Jul 20, 2018
BACKGROUND: There is limited consensus regarding risk factors for postoperative bleeding. The objective of this work was to investigate the capability of machine learning techniques in combination with practice-based longitudinal electronic medical r...
Optimizing Autoencoders for Learning Deep Representations From Health Data.
IEEE journal of biomedical and health informatics
Jul 17, 2018
Analyzing patients' health data using machine learning techniques can improve both patient outcomes and hospital operations. However, heterogeneous patient data (e.g., vital signs) and inefficient feature learning methods affect the implementation of...
A review of statistical and machine learning methods for modeling cancer risk using structured clinical data.
Artificial intelligence in medicine
Jul 14, 2018
Advancements are constantly being made in oncology, improving prevention and treatment of cancers. To help reduce the impact and deadliness of cancers, they must be detected early. Additionally, there is a risk of cancers recurring after potentially ...
Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.
BMC emergency medicine
Jul 3, 2018
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...
Natural Language Processing for EHR-Based Computational Phenotyping.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 25, 2018
This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping. NLP-based computational phenotyping has numerous applications including diagnosis categorization, no...
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