Battle of the Bots: Solving Clinical Cases in Osteoarticular Infections With Large Language Models DOI Creative Commons
Fabio Borgonovo, Takahiro Matsuo, Francesco Petri

и другие.

Mayo Clinic Proceedings Digital Health, Год журнала: 2025, Номер unknown, С. 100230 - 100230

Опубликована: Май 1, 2025

Язык: Английский

AI in Breast Cancer Imaging: An Update and Future Trends DOI Creative Commons
Yizhou Chen, Xiaoliang Shao, Kuangyu Shi

и другие.

Seminars in Nuclear Medicine, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

3
An overview of methods and techniques in multimodal data fusion with application to healthcare DOI
Siwar Chaabene, Amal Boudaya, Bassem Bouaziz

и другие.

International Journal of Data Science and Analytics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 10, 2025

Язык: Английский

Процитировано

2
From screens to scenes: A survey of embodied AI in healthcare DOI
Yihao Liu, Xu Cao, Tingting Chen

и другие.

Information Fusion, Год журнала: 2025, Номер unknown, С. 103033 - 103033

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2
A review of medical text analysis: Theory and practice DOI
Yani Chen, Chunwu Zhang, Ruibin Bai

и другие.

Information Fusion, Год журнала: 2025, Номер unknown, С. 103024 - 103024

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1
Evaluating ChatGPT-4 for the Interpretation of Images from Several Diagnostic Techniques in Gastroenterology DOI Open Access
Miguel Mascarenhas, Tiago Ribeiro, B Agudo

и другие.

Journal of Clinical Medicine, Год журнала: 2025, Номер 14(2), С. 572 - 572

Опубликована: Янв. 17, 2025

Background: Several artificial intelligence systems based on large language models (LLMs) have been commercially developed, with recent interest in integrating them for clinical questions. Recent versions now include image analysis capacity, but their performance gastroenterology remains untested. This study assesses ChatGPT-4's interpreting images. Methods: A total of 740 images from five procedures-capsule endoscopy (CE), device-assisted enteroscopy (DAE), endoscopic ultrasound (EUS), digital single-operator cholangioscopy (DSOC), and high-resolution anoscopy (HRA)-were included analyzed by ChatGPT-4 using a predefined prompt each. predictions were compared to gold standard diagnoses. Statistical analyses accuracy, sensitivity, specificity, positive predictive value (PPV), negative (NPV), area under the curve (AUC). Results: For CE, demonstrated accuracies ranging 50.0% 90.0%, AUCs 0.50-0.90. DAE, model an accuracy 67.0% (AUC 0.670). EUS, system showed 0.488 0.550 differentiation between pancreatic cystic solid lesions, respectively. The LLM differentiated benign malignant biliary strictures AUC 0.550. HRA, overall 47.5% 67.5%. Conclusions: suboptimal diagnostic interpretation across several techniques, highlighting need continuous improvement before adoption.

Язык: Английский

Процитировано

0
Evaluating Ai-Generated Patient Education Materials for Spinal Surgeries: Comparative Analysis of Readability and Discern Quality Across Chatgpt and Deepseek Models DOI
Mi Zhou, Yunfeng Pan, Yuye Zhang

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Reproduction of Original Glioblastoma and Brain Metastasis Research Findings Using Synthetic Data DOI Creative Commons
William Davalan, Roy Khalaf, Roberto J. Diaz

и другие.

World Neurosurgery, Год журнала: 2025, Номер 196, С. 123808 - 123808

Опубликована: Март 13, 2025

Язык: Английский

Процитировано

0
Vista: Vision-Text Alignment Model with Contrastive Learning Using Multimodal Data for Evidence-Driven, Reliable, and Explainable Alzheimer's Disease Diagnosis DOI
Duy-Cat Can,

Linh D. Dang,

Quang-Huy Tang

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine DOI Creative Commons
Sakhaa B. Alsaedi, Xin Gao, Takashi Gojobori

и другие.

FEBS Open Bio, Год журнала: 2025, Номер unknown

Опубликована: Фев. 24, 2025

Medical digital twins (MDTs) are virtual representations of patients that simulate the biological, physiological, and clinical processes individuals to enable personalized medicine. With increasing complexity omics data, particularly multiomics, there is a growing need for advanced computational frameworks interpret these data effectively. Foundation models (FMs), large‐scale machine learning pretrained on diverse types, have recently emerged as powerful tools improving interpretability decision‐making in precision This review discusses integration FMs into MDT systems, their role enhancing multiomics data. We examine current challenges, recent advancements, future opportunities leveraging analysis MDTs, with focus application

Язык: Английский

Процитировано

0
Evaluating AI-generated patient education materials for spinal surgeries: Comparative analysis of readability and DISCERN quality across ChatGPT and deepseek models DOI Creative Commons
Mi Zhou, Yunfeng Pan, Yuye Zhang

и другие.

International Journal of Medical Informatics, Год журнала: 2025, Номер unknown, С. 105871 - 105871

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0