AIMC Topic: Natural Language Processing

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Exploring the Perspectives of Older Adults on a Digital Brain Health Platform Using Natural Language Processing: Cohort Study.

JMIR formative research
BACKGROUND: Although digital technology represents a growing field aiming to revolutionize early Alzheimer disease risk prediction and monitoring, the perspectives of older adults on an integrated digital brain health platform have not been investiga...

Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic.

Current urology reports
PURPOSE OF REVIEW: In modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time...

Automatic TNM staging of colorectal cancer radiology reports using pre-trained language models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer is one of the major causes of cancer death worldwide. Essential for prognosis and treatment planning, TNM staging offers critical insights into the advancement of colorectal cancer. However, manual TNM stag...

Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials.

Circulation. Heart failure
BACKGROUND: Medical record review by a physician clinical events committee is the gold standard for identifying cardiovascular outcomes in clinical trials, but is labor-intensive and poorly reproducible. Automated outcome adjudication by artificial i...

Optimizing automated compliance checking with ontology-enhanced natural language processing: Case in the fire safety domain.

Journal of environmental management
The fire safety compliance checking (FSCC) plays a crucial role in ensuring the quality of fire engineering design and eliminating inherent fire hazards. It requires an objective and rational interpretation of fire regulations. However, the texts of ...

Examining the Role of Large Language Models in Orthopedics: Systematic Review.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) can understand natural language and generate corresponding text, images, and even videos based on prompts, which holds great potential in medical scenarios. Orthopedics is a significant branch of medicine, and...

AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges.

Journal of medical Internet research
BACKGROUND: Mental health disorders are currently the main contributor to poor quality of life and years lived with disability. Symptoms common to many mental health disorders lead to impairments or changes in the use of language, which are observabl...

MaskDGNets: Masked-attention guided dynamic graph aggregation network for event extraction.

PloS one
Considering that the traditional deep learning event extraction method ignores the correlation between word features and sequence information, it cannot fully explore the hidden associations between events and events and between events and primary at...

Enhancing systematic review efficiency in hand surgery using artificial intelligence (natural language processing) for abstract screening.

The Journal of hand surgery, European volume
The aim of the present study was to train a natural language processing model to recognize key text elements from research abstracts related to hand surgery, enhancing the efficiency of systematic review screening. A sample of 1600 abstracts from a s...

Extracting social determinants of health from inpatient electronic medical records using natural language processing.

Journal of epidemiology and population health
BACKGROUND: Social determinants of health (SDOH) have been shown to be important predictors of health outcomes. Here we developed methods to extract them from inpatient electronic medical record (EMR) data using techniques compatible with current EMR...