AIMC Topic: Natural Language Processing

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Who Tweets for the autistic community? A natural language processing-driven investigation.

Autism : the international journal of research and practice
The formation of autism advocacy organisations led by family members of autistic individuals led to intense criticism from some parts of the autistic community. In response to what was perceived as a misrepresentation of their interests, autistic ind...

Explainability Enhanced Machine Learning Model for Classifying Intellectual Disability and Attention-Deficit/Hyperactivity Disorder With Psychological Test Reports.

Journal of Korean medical science
BACKGROUND: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/hyperactivity disorder (ADHD). However, these reports can have several pr...

Optimising window size of semantic of classification model for identification of in-text citations based on context and intent.

PloS one
Citations in scientific literature act as channels for the sharing, transfer, and development of scientific knowledge. However, not all citations hold the same significance. Numerous taxonomies and machine learning models have been developed to analy...

CLIP in medical imaging: A survey.

Medical image analysis
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising results across various tasks due to its generalizability and interpretabil...

Artificial intelligence in chronic kidney disease management: a scoping review.

Theranostics
Chronic kidney disease (CKD) is a major public health problem worldwide associated with cardiovascular disease, renal failure, and mortality. To effectively address this growing burden, innovative solutions to management are urgently required. We co...

Natural Language Processing to Extract Head and Neck Cancer Data From Unstructured Electronic Health Records.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: Patient data is frequently stored as unstructured data within Electronic Health Records (EHRs), requiring manual curation. AI tools using Natural Language Processing (NLP) may rapidly curate accurate real-world unstructured EHRs to enrich datas...

Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.

Journal of psychopathology and clinical science
Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use an...

Studying memory narratives with natural language processing.

Trends in cognitive sciences
Cognitive neuroscience research has begun to use natural language processing (NLP) to examine memory narratives with the hopes of gaining a nuanced understanding of the mechanisms underlying differences in memory recall, both across groups and tasks....

The Role of AI in Modern Hernia Surgery: A Review and Practical Insights.

Surgical innovation
BackgroundArtificial intelligence (AI) is revolutionizing various aspects of health care, particularly in the surgical field, where it offers significant potential for improving surgical risk assessment, predictive analytics, and research advancement...

Synthetic Data-Driven Approaches for Chinese Medical Abstract Sentence Classification: Computational Study.

JMIR formative research
BACKGROUND: Medical abstract sentence classification is crucial for enhancing medical database searches, literature reviews, and generating new abstracts. However, Chinese medical abstract classification research is hindered by a lack of suitable dat...