To identify clinical features that predict the risk of meeting difficult-to-treat (D2T) rheumatoid arthritis (RA) definition in advance. This retrospective analysis included RA patients from the ATTRA registry who initiated biologic (b-) or targeted ...
This study aimed to identify candidate diagnostic miRNAs from the serum of colorectal cancer (CRC) patients using Boruta, a wrapper-based feature selection technique, in combination with decision tree-based machine learning methods. We analyzed three...
To avert criticism and losses of trust, robots that adopt social roles in the near future will have to be aware of and follow the norms of the communities in which they operate. However, norms often conflict with one another, and resolving such confl...
The multidimensional nature of schizophrenia requires a comprehensive exploration of the functional and structural brain networks. While prior research has provided valuable insights into these aspects, our study goes a step further to investigate th...
The rostral anterior cingulate cortex (rACC) has been identified as a key region in treatment-resistant depression (TRD), potentially influencing the adaptive interplay between the default mode network and other critical neural networks. This study a...
INTRODUCTION: Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental car...
OBJECTIVE: To develop and validate prediction models for peak oxygen uptake (VO₂peak) in patients with coronary heart disease (CHD) using submaximal cardiopulmonary exercise testing (CPET) indicators and deep learning methods.
Journal of cancer research and clinical oncology
Oct 4, 2025
PURPOSE: The integration of artificial intelligence (AI) with hyperspectral imaging (HSI) offers a promising avenue for improving pre-therapeutic prognosis, a key factor in optimizing cancer treatment strategies. This study explores the potential of ...
BACKGROUND: Hemophagocytic lymphohistiocytosis (HLH) is associated with high mortality rates. This study was conducted to develop and validate a predictive model for adult HLH patients at high risk of six months mortality using machine learning (ML) ...
OBJECTIVE: This study aims to develop multiple machine learning models for predicting hypothermia risk in laparoscopic surgery and to perform interpretability analysis of the best-performing model. Our goal is to provide robust decision support for c...
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