AIMC Topic: Practice Guidelines as Topic

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Validation of the Behavior of a Knowledge Base Implementing Clinical Guidelines for Point-of-Care Antiretroviral Toxicity Monitoring.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study investigated the automated detection of antiretroviral toxicities in structured electronic health records data. The evaluation compared responses generated by 5 clinical pharmacists and 1 prototype knowledge-based application for 15 random...

Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning.

Artificial intelligence in medicine
The conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in the diagnosis and the recommendations, and managing clinical equipoise situations. Personalized con...

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

The Lancet. Respiratory medicine
BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumoni...

Using preference learning for detecting inconsistencies in clinical practice guidelines: Methods and application to antibiotherapy.

Artificial intelligence in medicine
Clinical practice guidelines provide evidence-based recommendations. However, many problems are reported, such as contradictions and inconsistencies. For example, guidelines recommend sulfamethoxazole/trimethoprim in child sinusitis, but they also st...

Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.

Current hypertension reports
PURPOSE OF REVIEW: Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hyperte...

Representing and querying now-relative relational medical data.

Artificial intelligence in medicine
Temporal information plays a crucial role in medicine. Patients' clinical records are intrinsically temporal. Thus, in Medical Informatics there is an increasing need to store, support and query temporal data (particularly in relational databases), i...

Provider-specific quality measurement for ERCP using natural language processing.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Natural language processing (NLP) is an information retrieval technique that has been shown to accurately identify quality measures for colonoscopy. There are no systematic methods by which to track adherence to quality measures ...

Analyzing interactions on combining multiple clinical guidelines.

Artificial intelligence in medicine
Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recommendations meant to address each condition. Although some approaches have been proposed to address this issue, importa...

Automatic Generation of Conditional Diagnostic Guidelines.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The diagnostic workup for many diseases can be extraordinarily nuanced, and as such reference material text often contains extensive information regarding when it is appropriate to have a patient undergo a given procedure. In this work we employ a th...