AIMC Topic: Substance-Related Disorders
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Utilizing RAG and GPT-4 for Extraction of Substance Use Information from Clinical Notes.
Studies in health technology and informatics
Nov 22, 2024
This research investigates the application of a hybrid Retrieval-Augmented Generation (RAG) and Generative Pre-trained Transformer (GPT) pipeline for extracting and categorizing substance use information from unstructured clinical notes. The aim is t...
From Notes to Knowledge: Deciphering Perioperative Risky Substance Use through Natural Language Processing.
Anesthesiology
Nov 1, 2024
Natural language processing to identify substance misuse in the electronic health record.
The Lancet. Digital health
Jun 1, 2022
Application of bi-modal signal in the classification and recognition of drug addiction degree based on machine learning.
Mathematical biosciences and engineering : MBE
Aug 20, 2021
Most studies on drug addiction degree are made based on statistical scales, addicts' account, and subjective judgement of rehabilitation doctors. No objective, quantified evaluation has been made. This paper uses devises the synchronous bimodal signa...
Machine learning-based outcome prediction and novel hypotheses generation for substance use disorder treatment.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: Substance use disorder is a critical public health issue. Discovering the synergies among factors impacting treatment program success can help governments and treatment facilities develop effective policies. In this work, we propose a nove...
Machine-learning approaches to substance-abuse research: emerging trends and their implications.
Current opinion in psychiatry
Jul 1, 2020
PURPOSE OF REVIEW: To provide an accessible overview of some of the most recent trends in the application of machine learning to the field of substance use disorders and their implications for future research and practice.
Innovative Identification of Substance Use Predictors: Machine Learning in a National Sample of Mexican Children.
Prevention science : the official journal of the Society for Prevention Research
Feb 1, 2020
Machine learning provides a method of identifying factors that discriminate between substance users and non-users potentially improving our ability to match need with available prevention services within context with limited resources. Our aim was to...
Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2019
OBJECTIVE: Our objective is to develop algorithms for encoding clinical text into representations that can be used for a variety of phenotyping tasks.
Extracting Alcohol and Substance Abuse Status from Clinical Notes: The Added Value of Nursing Data.
Studies in health technology and informatics
Aug 21, 2019
We applied an open source natural language processing (NLP) system "NimbleMiner" to identify clinical notes with mentions of alcohol and substance abuse. NimbleMiner allows users to rapidly discover clinical vocabularies (using word embedding model) ...
Factors Associated with HIV Viral Suppression Among Transgender Women in Lima, Peru.
LGBT health
Jan 1, 2018
PURPOSE: Globally, transgender women (TGW) experience a high burden of adverse health outcomes, including a high prevalence of HIV and sexually transmitted infections (STIs) as well as psychiatric disorders and substance use disorders. To address gap...
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