AIMC Topic: Electronic Health Records

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Confidence-linked and uncertainty-based staged framework for phenotype validation using large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study develops and validates the confidence-linked and uncertainty-based staged (CLUES) framework by integrating large language models (LLMs) with uncertainty quantification to assist manual chart review while ensuring reliability th...

Optimizing surgical efficiency: predicting case duration of common general surgery procedures using machine learning.

Surgical endoscopy
BACKGROUND: Accurate prediction of surgical duration is critical to optimizing use of operating room resources. Currently, cases are scheduled using subjective estimates of length by surgeons, relying heavily on prior experience. This study aims to d...

Digitizing audiograms with deep learning: structured data extraction and pseudonymization for hearing big data.

Hearing research
PURPOSE: hearing loss relies on pure-tone audiometry (PTA); however, audiograms are often stored as unstructured images, limiting their integration into electronic medical records (EMRs) and common data models (CDMs). This study developed a deep lear...

[Taking digital healthcare to the next level: what practices and clinics need for digitalization!].

Urologie (Heidelberg, Germany)
BACKGROUND: Digitalization in urology is bringing about profound changes. While artificial intelligence (AI)-supported diagnoses, telemedical consultations and electronic patient files offer promising advances, challenges remain in the areas of techn...

Neurologists and Clinical Informatics: Realizing the Potential of Digital Medicine.

Seminars in neurology
Clinical informatics (CI) is an emerging field within biomedical informatics that sits at the intersection of clinical care, health systems, and health information technology (IT). CI emphasizes how individuals (neurologists, patients, staff) interac...

Differential dementia detection from multimodal brain images in a real-world dataset.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Artificial intelligence (AI) models have been applied to differential dementia detection tasks in brain images from curated, high-quality benchmark databases, but not real-world data in hospitals.

The use of generative artificial intelligence-based dictation in a neurosurgical practice: a pilot study.

Neurosurgical focus
OBJECTIVE: Document dictation remains a significant clinical burden and generative artificial intelligence (AI) systems utilizing transformer-based technology offer efficient speech processing methods that could streamline clinical documentation. Thi...

Dynamic few-shot prompting for clinical note section classification using lightweight, open-source large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Unlocking clinical information embedded in clinical notes has been hindered to a significant degree by domain-specific and context-sensitive language. Identification of note sections and structural document elements has been shown to impro...

Biomedical text normalization through generative modeling.

Journal of biomedical informatics
OBJECTIVE: A large proportion of electronic health record (EHR) data consists of unstructured medical language text. The formatting of this text is often flexible and inconsistent, making it challenging to use for predictive modeling, clinical decisi...

Healing with hierarchy: Hierarchical attention empowered graph neural networks for predictive analysis in medical data.

Artificial intelligence in medicine
In healthcare, predictive analysis using unstructured medical data is crucial for gaining insights into patient conditions and outcomes. However, unstructured data, which contains valuable patient information such as symptoms and medical histories, o...