Practice Management

Reimbursement

Latest AI and machine learning research in reimbursement for healthcare professionals.

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A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes.

BACKGROUND: International Classification of Diseases (ICD) codes utilized for congenital heart defec...

Using Natural Language Processing and Machine Learning to classify the status of kidney allograft in Electronic Medical Records written in Spanish.

INTRODUCTION: Accurate identification of graft loss in Electronic Medical Records of kidney transpla...

What Kind of Transformer Models to Use for the ICD-10 Codes Classification Task.

Coding according to the International Classification of Diseases (ICD)-10 and its clinical modificat...

Term Candidate Generation to Enrich Clinical Terminologies with Large Language Models.

Annotated language resources derived from clinical routine documentation form an intriguing asset fo...

Towards the development of a FAIR-compliant biomedical ontology for colorectal cancer.

Despite the widespread development of ontologies in many domains of healthcare, the field of colorec...

DRGKB: a knowledgebase of worldwide diagnosis-related groups' practices for comparison, evaluation and knowledge-guided application.

As a prospective payment method, diagnosis-related groups (DRGs)'s implementation has varying effect...

The potential of artificial intelligence to revolutionize health care delivery, research, and education in cardiac electrophysiology.

The field of electrophysiology (EP) has benefited from numerous seminal innovations and discoveries ...

Development of a Method for Automatic Matching of Unstructured Medical Data to ICD-10 Codes.

Inconsistent disease coding standards in medicine create hurdles in data exchange and analysis. This...

Enhancing Semantic and Structure Modeling of Diseases for Diagnosis Prediction.

Electronic Health Records (EHRs) are valuable healthcare data, aiding researchers and doctors in imp...

The New Emerging Treatment Choice for Major Depressive Disorders: Digital Therapeutics.

The chapter provides an in-depth analysis of digital therapeutics (DTx) as a revolutionary approach ...

Data-Driven Identification of Clinical Real-World Expressions Linked to ICD.

A semi-structured clinical problem list containing ∼1.9 million de-identified entries linked to ICD-...

Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment.

Clinical information systems have become large repositories for semi-structured and partly annotated...

Clinical Artificial Intelligence Applications in Radiology: Neuro.

Radiologists have been at the forefront of the digitization process in medicine. Artificial intellig...

A Deep Learning Framework for Automated ICD-10 Coding.

The International Statistical Classification of Diseases and Related Health Problems (ICD) is one of...

[Robot-assisted head and neck surgery].

Robot-assisted surgery (RAS) has already been approved for several clinical applications in head and...

Artificial intelligence in colonoscopy - Now on the market. What's next?

Adoption of artificial intelligence (AI) in clinical medicine is revolutionizing daily practice. In ...

eHealth and Clinical Documentation Systems.

eHealth is the use of modern information and communication technology (ICT) for trans-institutional ...

Supervised Learning for the ICD-10 Coding of French Clinical Narratives.

Automatic detection of ICD-10 codes in clinical documents has become a necessity. In this article, a...

A Semi-Automated Approach for Multilingual Terminology Matching: Mapping the French Version of the ICD-10 to the ICD-10 CM.

The aim of this study was to develop a simple method to map the French International Statistical Cla...

Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records.

OBJECTIVES: To develop classification algorithms that accurately identify axial SpA (axSpA) patients...

Classification of Current Procedural Terminology Codes from Electronic Health Record Data Using Machine Learning.

BACKGROUND: Accurate anesthesiology procedure code data are essential to quality improvement, resear...

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