AI Medical Compendium Topic:
Electronic Health Records

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Statistical inference for natural language processing algorithms with a demonstration using type 2 diabetes prediction from electronic health record notes.

Biometrics
The pointwise mutual information statistic (PMI), which measures how often two words occur together in a document corpus, is a cornerstone of recently proposed popular natural language processing algorithms such as word2vec. PMI and word2vec reveal s...

Artificial Intelligence and Mechanistic Modeling for Clinical Decision Making in Oncology.

Clinical pharmacology and therapeutics
The amount of "big" data generated in clinical oncology, whether from molecular, imaging, pharmacological, or biological origin, brings novel challenges. To mine efficiently this source of information, mathematical models able to produce predictive a...

Explainable artificial intelligence model to predict acute critical illness from electronic health records.

Nature communications
Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these pa...

Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data.

Annals of emergency medicine
STUDY OBJECTIVE: Acute kidney injury occurs commonly and is a leading cause of prolonged hospitalization, development and progression of chronic kidney disease, and death. Early acute kidney injury treatment can improve outcomes. However, current dec...

Prediction on critically ill patients: The role of "big data".

Journal of critical care
Accurate outcome prediction in Intensive Care Units (ICUs) would allow for better treatment planning, risk adjustment of study populations, and overall improvements in patient care. In the past, prognostic models have focused on mortality using simpl...

RAHM: Relation augmented hierarchical multi-task learning framework for reasonable medication stocking.

Journal of biomedical informatics
As an important task in digital preventive healthcare management, especially in the secondary prevention stage, active medication stocking refers to the process of preparing necessary medications in advance according to the predicted disease progress...

Extraction of temporal relations from clinical free text: A systematic review of current approaches.

Journal of biomedical informatics
BACKGROUND: Temporal relations between clinical events play an important role in clinical assessment and decision making. Extracting such relations from free text data is a challenging task because it lies on between medical natural language processi...

Identification of Patients with Heart Failure in Large Datasets.

Heart failure clinics
Large registries, administrative data, and the electronic health record (EHR) offer opportunities to identify patients with heart failure, which can be used for research purposes, process improvement, and optimal care delivery. Identification of case...