Practice Management

Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine.

UNLABELLED: Since the publication of its 2020 position statement on artificial intelligence (AI) in ...

A comprehensive review and evaluation of graph neural networks for non-coding RNA and complex disease associations.

Non-coding RNAs (ncRNAs) play a critical role in the occurrence and development of numerous human di...

A Hybrid AI-Based Method for ICD Classification of Medical Documents.

Automatic document classification is a common problem that has successfully been addressed with mach...

Six tips for better coding with ChatGPT.

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...

Artificial intelligence chatbots will revolutionize how cancer patients access information: ChatGPT represents a paradigm-shift.

On November 30, 2022, OpenAI enabled public access to ChatGPT, a next-generation artificial intellig...

Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.

From basic research to the bedside, precise terminology is key to advancing medicine and ensuring op...

Discovering misannotated lncRNAs using deep learning training dynamics.

MOTIVATION: Recent experimental evidence has shown that some long non-coding RNAs (lncRNAs) contain ...

TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning.

MOTIVATION: Analysis of whole-genome sequencing (WGS) for genetics is still a challenge due to the l...

Identification of Patients With Metastatic Prostate Cancer With Natural Language Processing and Machine Learning.

PURPOSE: Understanding treatment patterns and effectiveness for patients with metastatic prostate ca...

Permitted Sets and Convex Coding in Nonthreshold Linear Networks.

Hebbian theory proposes that ensembles of neurons form a basis for neural processing. It is possible...

EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.

Discovering rare cancer driver genes is difficult because their mutational frequency is too low for ...

Conception, Development and Validation of Classification Methods for Coding Support of Rare Diseases Using Artificial Intelligence.

Automated coding of diseases can support hospitals in the billing of inpatient cases with the health...

Integrating Human Patterns of Qualitative Coding with Machine Learning: A Pilot Study Involving Technology-Induced Error Incident Reports.

The objective of this research was to develop a reproducible method of integrating human patterns of...

Deep learning tools are top performers in long non-coding RNA prediction.

The increasing amount of transcriptomic data has brought to light vast numbers of potential novel RN...

Predictive Coding Approximates Backprop Along Arbitrary Computation Graphs.

Backpropagation of error (backprop) is a powerful algorithm for training machine learning architectu...

Fighting against sudden cardiac death: need for a paradigm shift-Adding near-term prevention and pre-emptive action to long-term prevention.

More than 40 years after the first implantable cardioverter-defibrillator (ICD) implantation, sudden...

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements.

PURPOSE: Prior studies have demonstrated the significance of specific cis-regulatory variants in ret...

Reconstruction of human protein-coding gene functional association network based on machine learning.

Networks consisting of molecular interactions are intrinsically dynamical systems of an organism. Th...

DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning.

MOTIVATION: Structural genomic variants account for much of human variability and are involved in se...