Practice Management

Representation of non-coding RNA-mediated regulation of gene expression using the Gene Ontology.

Regulatory non-coding RNAs (ncRNAs) are increasingly recognized as integral to the control of biological processes. This is often through the targeted regulation of mRNA expression, but this is by no means the only mechanism through which regulatory ncRNAs act. The Gene Ontology (GO) has long been used for the systematic annotation of protein-coding and ncRNA gene function, but rapid progress in t...

De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.

BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tissue sarcoma investigation because of the availability of all clinical results and pathology reports. In the setting of soft tissue sarcoma, natural lan...

Machine Learning-Based Clustering Using a 12-Lead Electrocardiogram in Patients With a Implantable Cardioverter Defibrillator to Identify Future Ventricular Arrhythmia.

BACKGROUND: Implantable cardioverter defibrillators (ICDs) reduce mortality associated with ventricular arrhythmia in high-risk patients with cardiova...

Learning to segment self-generated from externally caused optic flow through sensorimotor mismatch circuits.

Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion nee...

Artificial Intelligence to Predict Billing Code Levels of Emergency Department Encounters.

STUDY OBJECTIVE: To use artificial intelligence (AI) to predict billing code levels for emergency department (ED) encounters.

Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning.

Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD) is a unique form of programmed cell death that i...

Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers link...

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molec...

Validation of anorexia nervosa and Bulimia nervosa diagnosis coding in Danish hospitals assisted by a natural language processing model.

INTRODUCTION: The Danish Health Care Registers rely on the International Statistical Classification of Diseases and Related Health Problems (ICD)-clas...

Comparison and benchmark of deep learning methods for non-coding RNA classification.

The involvement of non-coding RNAs in biological processes and diseases has made the exploration of their functions crucial. Most non-coding RNAs have...

A Pre-Voiding Alarm System Using Wearable Ultrasound and Machine Learning Algorithms for Children With Nocturnal Enuresis.

Nocturnal enuresis is a bothersome condition that affects many children and their caregivers. Post-voiding systems is of little value in training a ch...

A method for miRNA diffusion association prediction using machine learning decoding of multi-level heterogeneous graph Transformer encoded representations.

MicroRNAs (miRNAs) are a key class of endogenous non-coding RNAs that play a pivotal role in regulating diseases. Accurately predicting the intricate ...

[Automatic ICD-10 coding : Natural language processing for German MRI reports].

BACKGROUND: The medical coding of radiology reports is essential for a good quality of care and correct billing, but at the same time a complex and er...

ICDXML: enhancing ICD coding with probabilistic label trees and dynamic semantic representations.

Accurately assigning standardized diagnosis and procedure codes from clinical text is crucial for healthcare applications. However, this remains chall...

"Where No One Has Gone Before": Questions to Ensure the Ethical, Rigorous, and Thoughtful Application of Artificial Intelligence in the Analysis of HIV Research.

ChatGPT, an artificial intelligence (AI) system released by OpenAI on November 30th, 2022, has upended scientific and educational paradigms, reshaping...

Classification of Patients' Judgments of Their Physicians in Web-Based Written Reviews Using Natural Language Processing: Algorithm Development and Validation.

BACKGROUND: Patients increasingly rely on web-based physician reviews to choose a physician and share their experiences. However, the unstructured tex...

Developing and testing a framework for coding general practitioners' free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing.

BACKGROUND: Diagnoses entered by general practitioners into electronic medical records have great potential for research and practice, but unfortunate...

ARDSFlag: an NLP/machine learning algorithm to visualize and detect high-probability ARDS admissions independent of provider recognition and billing codes.

BACKGROUND: Despite the significance and prevalence of acute respiratory distress syndrome (ARDS), its detection remains highly variable and inconsist...

Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance.

UNLABELLED: The erythromycin resistance RNA methyltransferase () confers cross-resistance to all therapeutically important macrolides, lincosamides, a...

Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico scor...