AIMC Topic: Electronic Health Records
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Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records.
IEEE transactions on neural networks and learning systems
Apr 4, 2024
Observational causal inference is useful for decision-making in medicine when randomized clinical trials (RCTs) are infeasible or nongeneralizable. However, traditional approaches do not always deliver unconfounded causal conclusions in practice. The...
Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Apr 3, 2024
BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text su...
Classifying early infant feeding status from clinical notes using natural language processing and machine learning.
Scientific reports
Apr 3, 2024
The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status from clinical notes in the Epic electronic health records system. The primary outcome was the classi...
Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.
Clinical research in cardiology : official journal of the German Cardiac Society
Apr 2, 2024
BACKGROUND: Referral of patients with heart failure (HF) who are at high mortality risk for specialist evaluation is recommended. Yet, most tools for identifying such patients are difficult to implement in electronic health record (EHR) systems.
Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations.
Artificial intelligence in medicine
Mar 30, 2024
Healthcare organizations have realized that Artificial intelligence (AI) can provide a competitive edge through personalized patient experiences, improved patient outcomes, early diagnosis, augmented clinician capabilities, enhanced operational effic...
[Orthopedics and trauma surgery in the digital age].
Orthopadie (Heidelberg, Germany)
Mar 27, 2024
BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedicine, digital health applications, electronic patient records and artificial intelligence play a central role in this. These technologies have the pot...
Identification of pancreatic cancer risk factors from clinical notes using natural language processing.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Mar 26, 2024
OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of ris...
A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records.
Headache
Mar 25, 2024
OBJECTIVE: To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes.
Using machine learning models to predict falls in hospitalised adults.
International journal of medical informatics
Mar 23, 2024
BACKGROUND: Identifying patients at high risk of falling is crucial in implementing effective fall prevention programs. While the integration of information systems is becoming more widespread in the healthcare industry, it poses a significant challe...
Building large-scale registries from unstructured clinical notes using a low-resource natural language processing pipeline.
Artificial intelligence in medicine
Mar 22, 2024
Building clinical registries is an important step in clinical research and improvement of patient care quality. Natural Language Processing (NLP) methods have shown promising results in extracting valuable information from unstructured clinical notes...
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