AIMC Topic: Machine Learning

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Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Pediatric sepsis imposes a significant burden of morbidity and mortality among children. While the speedy application of existing supportive care measures can substantially improve outcomes, further improvements in delivering that care require tools ...

Understanding Heart Failure Patients EHR Clinical Features via SHAP Interpretation of Tree-Based Machine Learning Model Predictions.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Heart failure (HF) is a major cause of mortality. Accurately monitoring HF progress and adjusting therapies are critical for improving patient outcomes. An experienced cardiologist can make accurate HF stage diagnoses based on combination of symptoms...

A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, the long-term complications often remain undetected at the early stages of diagnosis. Developing a ma...

Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Despite impressive success of machine learning algorithms in clinical natural language processing (cNLP), rule-based approaches still have a prominent role. In this paper, we introduce medspaCy, an extensible, open-source cNLP library based on spaCy ...

Development and Evaluation of an Automated Approach to Detect Weight Abnormalities in Pediatric Weight Charts.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Inaccurate body weight measures can cause critical safety events in clinical settings as well as hindering utilization of clinical data for retrospective research. This study focused on developing a machine learning-based automated weight abnormality...

Weak Supervision for Affordable Modeling of Electrocardiogram Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Analysing electrocardiograms (ECGs) is an inexpensive and non-invasive, yet powerful way to diagnose heart disease. ECG studies using Machine Learning to automatically detect abnormal heartbeats so far depend on large, manually annotated datasets. Wh...

Using Machine Learning to Support Transfer of Best Practices in Healthcare.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The adoption of best practices has been shown to increase performance in healthcare institutions and is consistently demanded by both patients, payers, and external overseers. Nevertheless, transferring practices between healthcare organizations is a...

Comparing Deep Learning and Conventional Machine Learning Models for Predicting Mental Illness from History of Present Illness Notations.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Mental illness, a serious problem across the globe, requires multi-pronged solutions including effective computational models to predict illness. Mental illness diagnosis is complicated by the pronounced sharing of symptoms and mutual pre-disposition...

Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Advancing diagnostic testing capabilities such as clinical next generation sequencing methods offer the potential to diagnose, risk stratify, and guide specialized treatment, but must be balanced against the escalating costs of healthcare to identify...

Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Unhealthy alcohol use represents a major economic burden and cause of morbidity and mortality in the United States. Implementation of interventions for unhealthy alcohol use depends on the availability and accuracy of screening tools. Our group previ...