Lisa C Adams
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Explore the profile of Lisa C Adams including associated specialties, affiliations and a list of published articles.
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87
Citations
706
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Recent Articles
1.
Adams L, Bressem K
Radiol Artif Intell
. 2025 Mar;
7(2):e250016.
PMID: 40042400
No abstract available.
2.
Kim S, Schramm S, Adams L, Braren R, Bressem K, Keicher M, et al.
NPJ Digit Med
. 2025 Feb;
8(1):97.
PMID: 39934372
Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment,...
3.
Graf M, Bressem K, Adams L
Radiologie (Heidelb)
. 2025 Feb;
PMID: 39934245
Background: The rapid development of large language models (LLMs) opens up new possibilities for the automated processing of medical texts. Transforming unstructured radiology reports into structured data is crucial for...
4.
Busch F, Hoffmann L, Rueger C, van Dijk E, Kader R, Ortiz-Prado E, et al.
Commun Med (Lond)
. 2025 Jan;
5(1):26.
PMID: 39838160
Background: The introduction of large language models (LLMs) into clinical practice promises to improve patient education and empowerment, thereby personalizing medical care and broadening access to medical knowledge. Despite the...
5.
Mangarova D, Kaufmann J, Brangsch J, Kader A, Mockel J, Heyl J, et al.
Invest Radiol
. 2025 Jan;
PMID: 39804796
Introduction: Atherosclerosis is the underlying cause of multiple cardiovascular pathologies. The present-day clinical imaging modalities do not offer sufficient information on plaque composition or rupture risk. A disintegrin and metalloproteinase...
6.
Dorfner F, Vahldiek J, Donle L, Zhukov A, Xu L, Hantze H, et al.
RMD Open
. 2024 Dec;
10(4.
PMID: 39719299
Purpose: To examine whether incorporating anatomy-centred deep learning can improve generalisability and enable prediction of disease progression. Methods: This retrospective multicentre study included conventional pelvic radiographs of four different patient...
7.
Fast D, Adams L, Busch F, Fallon C, Huppertz M, Siepmann R, et al.
NPJ Digit Med
. 2024 Dec;
7(1):358.
PMID: 39668168
Autonomous Medical Evaluation for Guideline Adherence (AMEGA) is a comprehensive benchmark designed to evaluate large language models' adherence to medical guidelines across 20 diagnostic scenarios spanning 13 specialties. It includes...
8.
Busch F, Prucker P, Komenda A, Ziegelmayer S, Makowski M, Bressem K, et al.
Eur J Radiol
. 2024 Nov;
182:111827.
PMID: 39566177
Purpose: Large language models (LLMs) promise to streamline radiology reporting. With the release of OpenAI's GPT-4o (Generative Pre-trained Transformers-4 omni), which processes not only text but also speech, multimodal LLMs...
9.
Bayerl N, Adams L, Cavallaro A, Bauerle T, Schlicht M, Wullich B, et al.
Eur J Radiol
. 2024 Nov;
181:111790.
PMID: 39520837
Objective: This study aims to evaluate the diagnostic performance of a commercial, fully-automated, artificial intelligence (AI) driven software tool in identifying and grading prostate lesions in prostate MRI, using histopathological...
10.
Dorfner F, Jurgensen L, Donle L, Al Mohamad F, Bodenmann T, Cleveland M, et al.
Radiology
. 2024 Oct;
313(1):e241139.
PMID: 39470431
Background Rapid advances in large language models (LLMs) have led to the development of numerous commercial and open-source models. While recent publications have explored OpenAI's GPT-4 to extract information of...