AIMC Topic: Humans

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Improving Large Language Model Applications in the Medical and Nursing Domains With Retrieval-Augmented Generation: Scoping Review.

Journal of medical Internet research
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...

3D deep learning-based muscle volume quantification from thoracic CT as a surrogate for DXA-Derived appendicular muscle mass in older adults.

Aging clinical and experimental research
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...

Evaluation of inflammatory markers in survival analysis of patients undergoing radical cystectomy using machine learning.

World journal of urology
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...

Comparative investigation into flexible alginate-based hydrogel sponges with excellent biocompatibility and breathability for reliable strain and pressure sensors.

Mikrochimica acta
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...

Prognostic value of admission ROTEM in trauma: enhancing 30-day all-cause mortality prediction using machine learning.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
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...

Effectiveness of artificial intelligence-assisted colonoscopy in detecting and diagnosing colorectal tumors: a systematic review and network meta-analysis.

International journal of colorectal disease
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...

CRLS1 influences liver metastasis in colon cancer by regulating lipid metabolism pathways.

Functional & integrative genomics
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 ...

Aligning machines and minds: neural encoding for high-level visual cortices based on image captioning task.

Journal of neural engineering
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...

Machine learning-enhanced normal tissue complication probability modeling for late sciatic nerve toxicity prediction in carbon-ion radiotherapy: model development and clinical validation.

Physics in medicine and biology
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...

Machine learning-driven Diabetes Health Tracer (DHT): Optimizing prognosis using RaSK_GraDe and RaSK_GraDeL models.

PloS one
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...