AI Medical Compendium Topic:
Electronic Health Records

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Natural language processing of clinical mental health notes may add predictive value to existing suicide risk models.

Psychological medicine
BACKGROUND: This study evaluated whether natural language processing (NLP) of psychotherapy note text provides additional accuracy over and above currently used suicide prediction models.

The CLASSE GATOR (CLinical Acronym SenSE disambiGuATOR): A Method for predicting acronym sense from neonatal clinical notes.

International journal of medical informatics
OBJECTIVE: To develop an algorithm for identifying acronym 'sense' from clinical notes without requiring a clinically annotated training set.

Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work.

Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach.

BMC medical informatics and decision making
BACKGROUND: A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects relevant to the organization...

Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.

JAMA network open
IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-h...

Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enough blood to meet the needs of...

Customization scenarios for de-identification of clinical notes.

BMC medical informatics and decision making
BACKGROUND: Automated machine-learning systems are able to de-identify electronic medical records, including free-text clinical notes. Use of such systems would greatly boost the amount of data available to researchers, yet their deployment has been ...

Combining deep learning with token selection for patient phenotyping from electronic health records.

Scientific reports
Artificial intelligence provides the opportunity to reveal important information buried in large amounts of complex data. Electronic health records (eHRs) are a source of such big data that provide a multitude of health related clinical information a...

From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.

Seminars in musculoskeletal radiology
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...