AIMC Topic: Patient Discharge Summaries

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Prescription extraction using CRFs and word embeddings.

Journal of biomedical informatics
In medical practices, doctors detail patients' care plan via discharge summaries written in the form of unstructured free texts, which among the others contain medication names and prescription information. Extracting prescriptions from discharge sum...

Predicting early psychiatric readmission with natural language processing of narrative discharge summaries.

Translational psychiatry
The ability to predict psychiatric readmission would facilitate the development of interventions to reduce this risk, a major driver of psychiatric health-care costs. The symptoms or characteristics of illness course necessary to develop reliable pre...

Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...

GeMTeX's De-Identification in Action: Lessons Learned & Devil's Details.

Studies in health technology and informatics
INTRODUCTION: In 2024, the GeMTeX project launched the largest ever de-identification campaign for German-language clinical reports, and, as a pilot study, published GraSCCoPHI, the first de-identified German-language gold standard corpus of syntheti...

Prompting Is All You Need - Until It Isn't: Exploring the Limits of LLMs for Negation Detection in German Clinical Text.

Studies in health technology and informatics
INTRODUCTION: Detecting negations in clinical text is crucial for accurate documentation and decision-making.

Application of artificial intelligence (AI) in the creation of discharge summaries in psychiatric clinics.

International journal of psychiatry in medicine
BackgroundThe integration of artificial intelligence (AI; ChatGPT 4.0) into medical workflow presents a great potential to enhance efficiency and quality. The use of AI in the creation of discharge summaries is particularly promising. The course of e...

Automation of Trainable Datasets Generation for Medical-Specific Language Model: Using MIMIC-IV Discharge Notes.

Studies in health technology and informatics
This study introduces a novel approach for generating machine-generated instruction datasets for fine-tuning medical-specialized language models using MIMIC-IV discharge records. The study created a large-scale text dataset comprising instructions, c...

The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task on clinical concept normalization for clinical records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task track 3, focused on medical concept normalization (MCN) in clinical records. This track aimed to assess the state of the art...

Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)-based ranking for concept normalization.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Concept normalization, the task of linking phrases in text to concepts in an ontology, is useful for many downstream tasks including relation extraction, information retrieval, etc. We present a generate-and-rank concept normalization syst...

2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This article summarizes the preparation, organization, evaluation, and results of Track 2 of the 2018 National NLP Clinical Challenges shared task. Track 2 focused on extraction of adverse drug events (ADEs) from clinical records and evalu...