Practice Management

Integrated multiplexed assays of variant effect reveal determinants of catechol-O-methyltransferase gene expression.

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering s...

Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.

PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may be used. We assessed whether natural language processing (NLP), as an alternative approach, could more accurately identify lens pathology.

Brain-computer interface paradigms and neural coding.

Brain signal patterns generated in the central nervous system of brain-computer interface (BCI) users are closely related to BCI paradigms and neural ...

Automatic ICD-10-CM coding via Lambda-Scaled attention based deep learning model.

The International Classification of Diseases (ICD) serves as a global healthcare administration standard, with one of its editions being ICD-10-CM, an...

Exploring the advances of single-cell RNA sequencing in thyroid cancer: a narrative review.

Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial increase in occurrence in recent decades. To gain a comprehensiv...

Evaluation of deep learning-based depression detection using medical claims data.

Human accuracy in diagnosing psychiatric disorders is still low. Even though digitizing health care leads to more and more data, the successful adopti...

Machine Learning Facial Emotion Classifiers in Psychotherapy Research: A Proof-of-Concept Study.

BACKGROUND: New advances in the field of machine learning make it possible to track facial emotional expression with high resolution, including micro-...

Healthcare Professional Association Agency in Preparing for Artificial Intelligence: A Multiple-Case Study of Radiation Medicine and Medical Imaging in the Canadian context.

As artificial intelligence (AI) is increasingly integrated in healthcare, it is incumbent on healthcare professional associations (HPAs) to assist the...

How deep is the brain? The shallow brain hypothesis.

Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in dee...

Machine learning-derived cycle length variability metrics predict spontaneously terminating ventricular tachycardia in implantable cardioverter defibrillator recipients.

AIMS: Implantable cardioverter defibrillator (ICD) therapies have been associated with increased mortality and should be minimized when safe to do so....

TGDAUNet: Transformer and GCNN based dual-branch attention UNet for medical image segmentation.

Accurate and automatic segmentation of medical images is a key step in clinical diagnosis and analysis. Currently, the successful application of Trans...

Embedding-based terminology expansion via secondary use of large clinical real-world datasets.

A log-likelihood based co-occurrence analysis of ∼1.9 million de-identified ICD-10 codes and related short textual problem list entries generated poss...

TraumaICD Bidirectional Encoder Representation From Transformers: A Natural Language Processing Algorithm to Extract Injury International Classification of Diseases, 10th Edition Diagnosis Code From Free Text.

OBJECTIVE: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury International Classification of Diseases, ...

Successful Development of a Natural Language Processing Algorithm for Pancreatic Neoplasms and Associated Histologic Features.

OBJECTIVES: Natural language processing (NLP) algorithms can interpret unstructured text for commonly used terms and phrases. Pancreatic pathologies a...

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data.

With the advances in technology and data science, machine learning (ML) is being rapidly adopted by the health care sector. However, there is a lack o...

Application of specialized word embeddings and named entity and attribute recognition to the problem of unsupervised automated clinical coding.

Notes documented by clinicians, such as patient histories, hospital courses, lab reports and others are often annotated with standardized clinical cod...

Machine translation of standardised medical terminology using natural language processing: A scoping review.

Standardised medical terminologies are used to ensure accurate and consistent communication of information and to facilitate data exchange. Currently,...

Prediction of DNA Methylation based on Multi-dimensional feature encoding and double convolutional fully connected convolutional neural network.

DNA methylation takes on critical significance to the regulation of gene expression by affecting the stability of DNA and changing the structure of ch...

Multigranularity Label Prediction Model for Automatic International Classification of Diseases Coding in Clinical Text.

International Classification of Diseases (ICD) serves as the foundation for generating comparable global disease statistics across regions and over ti...

DeepSATA: A Deep Learning-Based Sequence Analyzer Incorporating the Transcription Factor Binding Affinity to Dissect the Effects of Non-Coding Genetic Variants.

Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic vari...