AI Medical Compendium Topic

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Decision Support Systems, Clinical

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Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach.

Journal of healthcare engineering
Digoxin is a high-alert medication because of its narrow therapeutic range and high drug-to-drug interactions (DDIs). Approximately 50% of digoxin toxicity cases are preventable, which motivated us to improve the treatment outcomes of digoxin. The ob...

Automated ontology generation framework powered by linked biomedical ontologies for disease-drug domain.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The exponential growth of the unstructured data available in biomedical literature, and Electronic Health Record (EHR), requires powerful novel technologies and architectures to unlock the information hidden in the unstructu...

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

BMC bioinformatics
BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors were more associated with the DR than others. If we can detect the DR related risk factors more acc...

Using Machine Learning to Aid the Interpretation of Urine Steroid Profiles.

Clinical chemistry
BACKGROUND: Urine steroid profiles are used in clinical practice for the diagnosis and monitoring of disorders of steroidogenesis and adrenal pathologies. Machine learning (ML) algorithms are powerful computational tools used extensively for the reco...

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...

Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...

Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

Applied clinical informatics
Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with s...

Fuzzy decision support systems to diagnose musculoskeletal disorders: A systematic literature review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Musculoskeletal disorders (MSDs) are one of the most important causes of disability with a high prevalence. The accurate and timely diagnosis of these disorders is often difficult. Clinical decision support systems (CDSSs) c...