AIMC Topic: Natural Language Processing

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Incremental and transformational climate change adaptation factors in agriculture worldwide: A comparative analysis using natural language processing.

PloS one
Climate change is projected to adversely affect agriculture worldwide. This requires farmers to adapt incrementally already early in the twenty-first century, and to pursue transformational adaptation to endure future climate-induced damages. Many ar...

Utilising Natural Language Processing to Identify Brain Tumor Patients for Clinical Trials: Development and Initial Evaluation.

World neurosurgery
BACKGROUND: Identifying patients eligible for clinical trials through eligibility screening is time and resource-intensive. Natural Language Processing (NLP) models may enhance clinical trial screening by extracting data from Electronic Health Record...

Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing.

BMC medical informatics and decision making
BACKGROUND: In this era of active online communication, patients increasingly share their healthcare experiences, concerns, and needs across digital platforms. Leveraging these vast repositories of real-world information, Digital Listening enables th...

Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center.

Journal of the American College of Surgeons
BACKGROUND: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on the det...

Large Language Model-Driven 3D Hyper-Realistic Interactive Intelligent Digital Human System.

Sensors (Basel, Switzerland)
Digital technologies are undergoing comprehensive integration across diverse domains and processes of the human economy, politics, culture, society, and ecological civilization. This integration brings forth novel concepts, formats, and models. In th...

Topicwise Separable Sentence Retrieval for Medical Report Generation.

IEEE transactions on medical imaging
Automated radiology reporting holds immense clinical potential in alleviating the burdensome workload of radiologists and mitigating diagnostic bias. Recently, retrieval-based report generation methods have garnered increasing attention. These method...

LHR-RFL: Linear Hybrid-Reward-Based Reinforced Focal Learning for Automatic Radiology Report Generation.

IEEE transactions on medical imaging
Radiology report generation that aims to accurately describe medical findings for given images, is pivotal in contemporary computer-aided diagnosis. Recently, despite considerable progress, current radiology report generation models still struggled t...

CoD-MIL: Chain-of-Diagnosis Prompting Multiple Instance Learning for Whole Slide Image Classification.

IEEE transactions on medical imaging
Multiple instance learning (MIL) has emerged as a prominent paradigm for processing the whole slide image with pyramid structure and giga-pixel size in digital pathology. However, existing attention-based MIL methods are primarily trained on the imag...

Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.

Cerebrovascular diseases extra
INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart review to screen for thrombolysis contraindications may be time-consuming and prone to errors. We developed and tested a large language model (LLM)-bas...

Current Applications and Developments of Natural Language Processing in Kidney Transplantation: A Scoping Review.

Transplantation proceedings
BACKGROUND AND OBJECTIVE: Natural language processing (NLP) is a subfield of artificial intelligence that enables computers to process human language. As most human interactions today involve the internet and electronic devices, NLP tools quickly bec...