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A simple clustering approach to map the human brain's cortical semantic network organization during task.
NeuroImage
Feb 18, 2025
Constructing task-state large-scale brain networks can enhance our understanding of the organization of brain functions during cognitive tasks. The primary goal of brain network partitioning is to cluster functionally homogeneous brain regions. Howev...
Explaining electroencephalogram channel and subband sensitivity for alcoholism detection.
Computers in biology and medicine
Feb 18, 2025
Alcoholism, a progressive loss of control over alcohol consumption, deteriorates mental and physical health over time. Automatic alcoholism detection can aid in early interventions and timely corrective actions. For this purpose, electroencephalogram...
Humans take the visuospatial perspective of robots and objects that imply social presence.
Acta psychologica
Feb 18, 2025
Visual perspective-taking (VPT) plays a crucial role in social interactions. Although the mechanisms behind VPT have been thoroughly studied in human-human interactions, there are only a few studies examining whether humans can also adopt the visuosp...
AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations.
Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
Feb 18, 2025
BACKGROUND: AI-aided home stethoscopes offer the opportunity of continuous remote monitoring of cystic fibrosis (CF) patients, reducing the need for clinic visits.
Intelligent Verification Tool for Surgical Information of Ophthalmic Patients: A Study Based on Artificial Intelligence Technology.
Journal of patient safety
Feb 18, 2025
OBJECTIVE: With the development of day surgery, the characteristics of "short, frequent and fast" ophthalmic surgery are becoming more prominent. However, nurses are not efficient in verifying patients' surgical information, and problems such as pati...
Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.
Cancer imaging : the official publication of the International Cancer Imaging Society
Feb 18, 2025
BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for precise treatment planning. This study aims to utilize convolutional neural networks based on dual-time-point F-FDG PET/CT to predict the malignant ris...
Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study.
BMC medical informatics and decision making
Feb 18, 2025
AIMS: Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus. Early identification of individuals at high risk of DPN is essential for successful early intervention. Traditional Chinese medicine (TCM) tongue diagnos...
Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward.
BMC medical education
Feb 18, 2025
BACKGROUND: Measuring artificial intelligence (AI) readiness among medical students is essential to assess how prepared future doctors are to work with AI technology. Therefore, this study aimed to examine the factors influencing AI readiness among m...
Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer.
BMC cancer
Feb 18, 2025
OBJECTIVE: This study aimed to evaluate the predictive value of implementing machine learning models based on ultrasound radiomics and clinicopathological features in the survival analysis of triple-negative breast cancer (TNBC) patients.
Predicting mother and newborn skin-to-skin contact using a machine learning approach.
BMC pregnancy and childbirth
Feb 18, 2025
BACKGROUND: Despite the known benefits of skin-to-skin contact (SSC), limited data exists on its implementation, especially its influencing factors. The current study was designed to use machine learning (ML) to identify the predictors of SSC.
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