BACKGROUND: Retrieval-augmented generation (RAG) is increasingly used to improve large language models in the medical and nursing domains. However, a comprehensive understanding of its specific architecture and applications in medical and nursing rea...
Aging clinical and experimental research
Oct 21, 2025
BACKGROUND: In order to identify patients with sarcopenia, the use of routine imaging could provide valuable support. One of the most common radiological examinations, especially in geriatric inpatient care, is CT thoracic imaging. Therefore, it woul...
BACKGROUND: We aimed to create a Machine learning (ML) model using patient demographic, clinical and pathological data for prediction of overall survival in patients treated with radical cystectomy (RC). Secondly, we evaluated whether inflammatory ma...
Flexible sensors with a porous hydrogel structure have attracted enormous attention for their extensive potential prospects in the fields of wearable electronics and human-machine interaction (HMI). Nevertheless, these sensors encounter significant c...
European journal of trauma and emergency surgery : official publication of the European Trauma Society
Oct 21, 2025
BACKGROUND: Haemorrhage is a leading cause of trauma death, yet early coagulation markers are rarely used to predict long-term outcomes. This study assessed whether a single admission rotational thromboelastometry (ROTEM) test could independently pre...
International journal of colorectal disease
Oct 21, 2025
BACKGROUND: The emergence of artificial intelligence (AI) has greatly promoted the development of the field of medical image analysis, but the potential benefits of AI-assisted colonoscopy and diagnosis (CADe/CADx) for the detection rate of colorecta...
Colon cancer is one of the leading causes of cancer-related mortality, with liver metastasis commonly complicating its progression and significantly worsening patient prognosis. This study aims to explore the relationship between liver metastasis in ...
Neural encoding of visual stimuli aims to predict brain responses in the visual cortex to different external inputs. Deep neural networks trained on relatively simple tasks such as image classification have been widely applied in neural encoding stud...
To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion rad...
Diabetes mellitus presents a significant global health challenge, particularly in regions like Pakistan, India, and Bangladesh. Machine learning (ML) techniques offer promising solutions for diabetes prediction, surpassing traditional methods in reli...
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