Latest AI and machine learning research in reimbursement for healthcare professionals.
INTRODUCTION: Adverse drug reaction (ADR) detection in hospitals is heavily reliant on spontaneous r...
An ontology offers a human-readable and machine-computable representation of the concepts in a domai...
This paper describes a method by which the Web Ontology Language (OWL) can be used to specify a high...
ICD encoded diagnoses are a popular criterion for eligibility algorithms for study cohort recruitmen...
Unplanned hospital readmissions are a burden to the healthcare system and to the patients. To lower ...
A capillary zone electrophoresis (CZE) method for the quantitation of captopril (CPT) using UV detec...
Pathology reports are a main source of information regarding cancer diagnosis and are commonly writt...
BACKGROUND: Multiple sclerosis (MS), a central nervous system disease in which nerve signals are dis...
BACKGROUND: Accurate identification of hepatocellular cancer (HCC) cases from automated data is need...
OBJECTIVES: The objective of this study was to use natural language processing (NLP) as a supplement...
This case involves a 76 year-old woman. A sigmoidectomy was performed for sigmoid colon cancer in Au...
To estimate the prevalence of problem opioid use, we used natural language processing (NLP) techniqu...
In Italy, ICD-9-CM is currently used for coding health conditions at hospital discharge, but ICD-10 ...
The Diagnostic and Statistical Manual (DSM) has served as the gold standard for psychiatric diagnosi...
This work develops an automated classifier of pathology reports which infers the topography and the ...
Self-service cohort discovery tools strive to provide intuitive interfaces to large Clinical Data Wa...
BACKGROUND: The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and d...