AI Medical Compendium Topic:
Electronic Health Records

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Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer's disease and related dementias.

International journal of medical informatics
BACKGROUND: Cognitive tests and biomarkers are the key information to assess the severity and track the progression of Alzheimer's' disease (AD) and AD-related dementias (AD/ADRD), yet, both are often only documented in clinical narratives of patient...

Transforming epilepsy research: A systematic review on natural language processing applications.

Epilepsia
Despite improved ancillary investigations in epilepsy care, patients' narratives remain indispensable for diagnosing and treatment monitoring. This wealth of information is typically stored in electronic health records and accumulated in medical jour...

MR-KPA: medication recommendation by combining knowledge-enhanced pre-training with a deep adversarial network.

BMC bioinformatics
BACKGROUND: Medication recommendation based on electronic medical record (EMR) is a research hot spot in smart healthcare. For developing computational medication recommendation methods based on EMR, an important challenge is the lack of a large numb...

Electronic Health Record Optimization for Artificial Intelligence.

Clinics in laboratory medicine
Laboratory clinical decision support (CDS) typically relies on data from the electronic health record (EHR). The implementation of a sustainable, effective laboratory CDS program requires a commitment to standardization and harmonization of key EHR d...

Clinical Application of Detecting COVID-19 Risks: A Natural Language Processing Approach.

Viruses
The clinical application of detecting COVID-19 factors is a challenging task. The existing named entity recognition models are usually trained on a limited set of named entities. Besides clinical, the non-clinical factors, such as social determinant ...

Using natural language processing to identify opioid use disorder in electronic health record data.

International journal of medical informatics
BACKGROUND: As opioid prescriptions have risen, there has also been an increase in opioid use disorder (OUD) and its adverse outcomes. Accurate and complete epidemiologic surveillance of OUD, to inform prevention strategies, presents challenges. The ...

Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data.

JAMA network open
IMPORTANCE: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest...

Practice-Based Learning and Improvement: Improving Morbidity and Mortality Review Using Natural Language Processing.

The Journal of surgical research
INTRODUCTION: Practice-Based Learning and Improvement, a core competency identified by the Accreditation Council for Graduate Medical Education, carries importance throughout a physician's career. Practice-Based Learning and Improvement is cultivated...

COMMUTE: Communication-efficient transfer learning for multi-site risk prediction.

Journal of biomedical informatics
OBJECTIVES: We propose a communication-efficient transfer learning approach (COMMUTE) that effectively incorporates multi-site healthcare data for training a risk prediction model in a target population of interest, accounting for challenges includin...

Using model explanations to guide deep learning models towards consistent explanations for EHR data.

Scientific reports
It has been shown that identical deep learning (DL) architectures will produce distinct explanations when trained with different hyperparameters that are orthogonal to the task (e.g. random seed, training set order). In domains such as healthcare and...