EHRs - Epidemiology

What are Electronic Health Records (EHRs)?

Electronic Health Records (EHRs) are digital versions of a patient’s paper chart. They contain comprehensive health information, including medical history, diagnoses, medications, treatment plans, immunization dates, and test results. EHR systems are designed to share information with other healthcare providers and organizations, such as laboratories, specialists, and pharmacies.

How Do EHRs Benefit Epidemiology?

In the field of

Relevant Publications

DNA-T: Deformable Neighborhood Attention Transformer for Irregular Medical Time Series.

Issue Release: 2024

External validation of three diabetes prediction scores in a Spanish cohort: does adding high risk for depression improve the validation of the FINDRISC score (FINDRISC-MOOD)?

Issue Release: 2024

TEE4EHR: Transformer event encoder for better representation learning in electronic health records.

Issue Release: 2024

A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.

Issue Release: 2024

Using Routinely Collected Electronic Healthcare Record Data to Investigate Fibrotic Multimorbidity in England.

Issue Release: 2024

Advancing equity in breast cancer care: natural language processing for analysing treatment outcomes in under-represented populations.

Issue Release: 2024

Inferring Population HIV Viral Load From a Single HIV Clinic\'s Electronic Health Record: Simulation Study With a Real-World Example.

Issue Release: 2024

A systematic evaluation of the performance of GPT-4 and PaLM2 to diagnose comorbidities in MIMIC-IV patients.

Issue Release: 2024

Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management.

Issue Release: 2024

Improving the quality of Persian clinical text with a novel spelling correction system.

Issue Release: 2024

Barriers to Optimal Clinician Guideline Adherence in Management of Markedly Elevated Blood Pressure: A Qualitative Study.

Issue Release: 2024

Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study.

Issue Release: 2024

Assessing placental membrane treatment efficiency in diabetic foot ulcers: Processing for retention versus lamination.

Issue Release: 2024

Predicting Glaucoma Surgical Outcomes Using Neural Networks and Machine Learning on Electronic Health Records.

Issue Release: 2024

Healthcare professionals\' perception on emergence of security threat using digital health technologies in healthcare delivery.

Issue Release: 2024

Associations between long-term exposure to air pollution and kidney function utilizing electronic healthcare records: a cross-sectional study.

Issue Release: 2024

Comparison of different definitions of traumatic brain injury: implications for cohort characteristics and survival in women, Philadelphia, USA.

Issue Release: 2024

Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models.

Issue Release: 2024

Large Language Models for Social Determinants of Health Information Extraction from Clinical Notes - A Generalizable Approach across Institutions.

Issue Release: 2024

Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data.

Issue Release: 2024

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