AIMC Topic: Natural Language Processing

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Extracting adverse drug events from clinical Notes: A systematic review of approaches used.

Journal of biomedical informatics
BACKGROUND: An adverse drug event (ADE) is any unfavorable effect that occurs due to the use of a drug. Extracting ADEs from unstructured clinical notes is essential to biomedical text extraction research because it helps with pharmacovigilance and p...

SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization.

Journal of biomedical informatics
Electronic health records (EHRs) store an extensive array of patient information, encompassing medical histories, diagnoses, treatments, and test outcomes. These records are crucial for enabling healthcare providers to make well-informed decisions re...

MAEF-Net: MLP Attention for Feature Enhancement in U-Net based Medical Image Segmentation Networks.

IEEE journal of biomedical and health informatics
Medical image segmentation plays an important role in diagnosis. Since the introduction of U-Net, numerous advancements have been implemented to enhance its performance and expand its applicability. The advent of Transformers in computer vision has l...

Large Language Models and Healthcare Alliance: Potential and Challenges of Two Representative Use Cases.

Annals of biomedical engineering
Large language models (LLMS) emerge as the most promising Natural Language Processing approach for clinical practice acceleration (i.e., diagnosis, prevention and treatment procedures). Similarly, intelligent conversational systems that leverage LLMS...

Advantages of transformer and its application for medical image segmentation: a survey.

Biomedical engineering online
PURPOSE: Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models. Transformer, a technology used in natu...

Automating the assessment of multicultural orientation through machine learning and natural language processing.

Psychotherapy (Chicago, Ill.)
Recent scholarship has highlighted the value of therapists adopting a multicultural orientation (MCO) within psychotherapy. A newly developed performance-based measure of MCO capacities exists (MCO-performance task [MCO-PT]) in which therapists respo...

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

American journal of ophthalmology
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...

Potential cognitive risks of generative transformer-based AI chatbots on higher order executive functions.

Neuropsychology
BACKGROUND: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use...

Bidirectional Encoder Representations from Transformers in Radiology: A Systematic Review of Natural Language Processing Applications.

Journal of the American College of Radiology : JACR
INTRODUCTION: Bidirectional Encoder Representations from Transformers (BERT), introduced in 2018, has revolutionized natural language processing. Its bidirectional understanding of word context has enabled innovative applications, notably in radiolog...