AIMC Topic: Adult

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Deep learning-powered multi-parametric ultrasound for classifying metastatic versus reactive axillary lymph nodes.

Breast cancer research : BCR
PURPOSE: To propose a multi-parametric ultrasound imaging-based deep learning method for accurately classifying metastatic and non-metastatic axillary lymph nodes in breast cancer patients.

Development and validation of a machine learning-based model for predicting radiation-induced hypothyroidism in nasopharyngeal carcinoma.

Radiation oncology (London, England)
BACKGROUND AND PURPOSE: This study aims to develop a robust and user-friendly prediction model for radiation-induced hypothyroidism (RIHT) in nasopharyngeal carcinoma (NPC) patients.

Prediction of postoperative haemorrhage after cerebral tumour surgery using machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Traditional diagnostic methods used by neurosurgeons are limited in their ability to address complex interactions. These limitations have necessitated the use of advanced artificial intelligence approaches capable of analyzing multidimens...

Application of multimodal integration to develop preoperative diagnostic models for borderline and malignant ovarian tumors.

Scientific reports
Malignant ovarian tumors (MOTs) and borderline ovarian tumors (BOTs) differ in treatment strategies and prognosis. However, accurate preoperative diagnosis remains challenging, and improving diagnostic accuracy is crucial. We developed and validated ...

Randomised controlled trial of VR-based observation meditation with AI coaching ('Otti') for stress reduction in university students in the United States: study protocol.

BMJ open
INTRODUCTION: Stress is a major health issue in contemporary society, and mindfulness-based approaches reduce stress and anxiety but face practical barriers to consistent practice; this protocol evaluates a Virtual Reality (VR)-based observation medi...

Requirements and Concerns of Remitted Individuals With Depression for an Early Relapse Detection mHealth App: Focus Group Study.

JMIR mHealth and uHealth
BACKGROUND: Major depressive disorder is often a recurrent condition, with a high risk of relapse for individuals remitted from depression. Early detection of relapse is critical to improve clinical outcomes. Mobile health (mHealth) technologies offe...

Heterogeneity of human insular cortex: five principles of functional organization across multiple cognitive domains.

Brain structure & function
The insular cortex serves as a critical hub for human cognition, but how its anatomically distinct subregions coordinate diverse cognitive, emotional, and social functions remains unclear. Using the Human Connectome Project's multi-task fMRI dataset ...

Identifying and predicting dietary patterns in the Dutch population using machine learning.

European journal of nutrition
PURPOSE: Nutritional epidemiological research is shifting its focus from individual nutrients to dietary patterns, which challenges traditional statistical methods. Here, we aim to apply various machine learning algorithms to identify and predict die...

Cardiovascular risk prediction in diabetes: a hybrid machine learning approach.

Biomedical physics & engineering express
Cardiovascular disease (CVD) is a major cause of morbidity and mortality in diabetic populations. Early detection of cardiovascular risk in diabetes is crucial to reduce complications, particularly in resource-limited settings. This study aimed to de...