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Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.

CNS neuroscience & therapeutics
AIM: This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas.

Using ChatGPT for Kidney Transplantation: Perceived Information Quality by Race and Education Levels.

Clinical transplantation
BACKGROUND: Kidney transplantation is a complex process requiring extensive preparation and ongoing monitoring. Artificial intelligence (AI)-powered chatbots hold potential for providing accessible health information, but our understanding of their r...

Detection of Cervical Foraminal Stenosis from Oblique Radiograph Using Convolutional Neural Network Algorithm.

Yonsei medical journal
PURPOSE: This study was conducted to develop a convolutional neural network (CNN) algorithm that can diagnose cervical foraminal stenosis using oblique radiographs and evaluate its accuracy.

External validation of the myocardial-ischaemic-injury-index machine learning algorithm for the early diagnosis of myocardial infarction: a multicentre cohort study.

The Lancet. Digital health
BACKGROUND: The myocardial-ischaemic-injury-index (MI) is a novel machine learning algorithm for the early diagnosis of type 1 non-ST-segment elevation myocardial infarction (NSTEMI). The performance of MI, both when using early serial blood draws (e...

Proteomic prediction of diverse incident diseases: a machine learning-guided biomarker discovery study using data from a prospective cohort study.

The Lancet. Digital health
BACKGROUND: Broad-capture proteomic technologies have the potential to improve disease prediction, enabling targeted prevention and management, but studies have so far been limited to very few selected diseases and have not evaluated predictive perfo...

Physician and Artificial Intelligence Chatbot Responses to Cancer Questions From Social Media.

JAMA oncology
IMPORTANCE: Artificial intelligence (AI) chatbots pose the opportunity to draft template responses to patient questions. However, the ability of chatbots to generate responses based on domain-specific knowledge of cancer remains to be tested.

Improving Automated Hemorrhage Detection at Sparse-View CT via U-Net-based Artifact Reduction.

Radiology. Artificial intelligence
Purpose To explore the potential benefits of deep learning-based artifact reduction in sparse-view cranial CT scans and its impact on automated hemorrhage detection. Materials and Methods In this retrospective study, a U-Net was trained for artifact ...

Performance of an Open-Source Large Language Model in Extracting Information from Free-Text Radiology Reports.

Radiology. Artificial intelligence
Purpose To assess the performance of a local open-source large language model (LLM) in various information extraction tasks from real-life emergency brain MRI reports. Materials and Methods All consecutive emergency brain MRI reports written in 2022 ...

A Machine Learning Algorithm Facilitates Prognosis Prediction and Treatment Selection for Barcelona Clinic Liver Cancer Stage C Hepatocellular Carcinoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) is required for appropriately determining patient prognosis and selecting treat...