Latest AI and machine learning research in practice management for healthcare professionals.
Extracting clinically useful information from free-text notes remains challenging due to their unstructured nature, while medical coding is still only partially automated. We present a two-stage pipeline for linking spans in clinical notes to Systematized Nomenclature of Medicine-Clinical Terminology (SNOMED CT) that combines fine-tuned sequence labeling with retrieval-augmented concept selection....
INTRODUCTION: Clinical narratives are difficult to process due to unstructured text, abbreviations, and jargon, which limit semantic interoperability. Converting them into knowledge graphs (KGs) and pruning SNOMED CT enables focused, interoperable representations without losing essential information. METHODS: KGs were built from the n2c2 2019 dataset using SNOMED CT and UMLS to model concept relat...
We evaluated six medium-sized generative models (Autoregressive Transformers and a Diffusion Language Model) on automated veterinary ICD-11 coding. Ge...
This work's objective is to support secondary use of unstructured clinical text data in research. We introduce a REDCap-integrated tool that enables s...
Large Language Models (LLMs) have shown remarkable capabilities in medical information extraction and data transformation tasks. However, their unstru...
BACKGROUND: Large language models have shown potential for supporting clinical reasoning, but their performance in open-ended diagnostic tasks remains...
Noncoding variants occur within noncoding genes as well as within the regulatory nontranslated regions of protein-coding genes. It is important to be ...
OBJECTIVES: The objective of this research was to examine the content and context-specific information diffusion patterns underlying communication per...
Companion animal disease surveillance now benefits from collated databases of electronic health records and artificial intelligence. This review exami...
INTRODUCTION: The combination of phototherapy (PTT/PDT) and immunotherapy holds promise for cancer treatment but is hindered by poor spatiotemporal co...
BACKGROUND: Urological care in Germany is undergoing transformation, while novel technologies with artificial intelligence (AI) have the potential to ...
BACKGROUND: Timely medical follow-up after a diagnosis of cognitive impairment, such as mild cognitive impairment (MCI) or dementia, is imperative for...
Background and PurposeMechanical ventilation (MV) occurs in a substantial subset of acute ischemic stroke (AIS) hospitalizations and is associated wit...
BACKGROUND: Heart failure (HF) decompensation is the leading cause of hospitalisations in developed countries and the third most common cause in Brazi...
BACKGROUND: Lifelong learning (LLL) is increasingly important for health care professionals, particularly within the field of orthodontics, driven by ...
Explainable Artificial Intelligence (XAI) has the potential to enhance clinical decision support (CDS) systems however, it remains unclear how XAI sys...
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common reason for admission to the intensive care unit (ICU), where accurate risk strati...
BACKGROUND: The management of type 2 diabetes requires sustained self-management across diet, physical activity, medication adherence, and blood gluco...
OBJECTIVE: Ambient artificial intelligence (AI) documentation is increasingly used to draft clinical notes from patient-provider conversations, but ho...
Red blood cell distribution width (RDW)-derived indicators have increasingly been recognized as biomarkers reflecting systemic inflammation and hemato...