Detailed social determinants of health (SDoH) is often buried within clinical text in EHRs. Most current NLP efforts for SDoH have limitations, investigating limited factors, deriving data from a single institution, using specific patient…
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Artificial Intelligence can mitigate the global shortage of medical diagnostic personnel but requires large-scale annotated datasets to train clinical algorithms. Natural Language Processing (NLP), including Large Language Models (LLMs), shows great potential for annotating…
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Integrating large language models (LLMs) into healthcare can enhance workflow efficiency and patient care by automating tasks such as summarising consultations. However, the fidelity between LLM outputs and ground truth information is vital to…
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Large-language models (LLMs) show promise for clinical note information extraction, but deployment challenges include high computational costs and privacy concerns. We used synthetic data distillation to fine-tune smaller, open-source LLMs to achieve performance comparable…
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Accurate medical decision-making is critical for both patients and clinicians. Patients often struggle to interpret their symptoms, determine their severity, and select the right specialist. Simultaneously, clinicians face challenges in integrating complex patient data…
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What Is Agentic AI?
Like other forms of artificial intelligence, agentic AI is only as accurate as the data that fuels it. It relies on “a digital ecosystem of large language models (LLMs), machine learning…
Critical findings in radiology reports are life threatening conditions that need to be communicated promptly to physicians for timely management of patients. Although challenging, advancements in natural language processing (NLP), particularly large language models…
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How ANNs Are Revolutionizing Medicine
Artificial Neural Networks (ANNs) have been quietly evolving since the 1950s, but their impact on healthcare has accelerated dramatically in recent years. Unlike modern Large Language Models (LLMs) like ChatGPT,…
Clinical trials are an essential component of drug development for new cancer treatments, yet the information required to determine a patient’s eligibility for enrollment is scattered in large amounts of unstructured text. Genomic biomarkers…
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The advent of large language models (LLMs) represents an enormous opportunity to revolutionize medical education. Via “synthetic education,” LLMs can be harnessed to generate novel content for medical education purposes, offering potentially unlimited resources…
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