AIMC Topic: Adult

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Deep learning and radiomics integration of photoacoustic/ultrasound imaging for non-invasive prediction of luminal and non-luminal breast cancer subtypes.

Breast cancer research : BCR
PURPOSE: This study aimed to develop a Deep Learning Radiomics integrated model (DLRN), which combines photoacoustic/ultrasound(PA/US)imaging with clinical and radiomics features to distinguish between luminal and non-luminal BC in a preoperative set...

Revolutionizing Wilson disease prognosis: a machine learning approach to predict acute-on-chronic liver failure.

Journal of translational medicine
BACKGROUND AND OBJECTIVES: Wilson disease (WD), an inherited copper metabolism disorder, is a cause of acute-on-chronic liver failure (ACLF), posing life-threatening risks due to rapid progression. This study aimed to develop a machine learning (ML)-...

Predictive models for live birth outcomes following fresh embryo transfer in assisted reproductive technologies using machine learning.

Journal of translational medicine
BACKGROUND: Infertility affects approximately 15% of couples globally, with assisted reproductive technologies (ARTs) becoming the primary interventions. Despite the growing use of ARTs, success rates have plateaued at around 30%, highlighting the ne...

Interpretable Machine Learning Model for Pulmonary Hypertension Risk Prediction: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Pulmonary hypertension (PH) is a progressive disorder characterized by elevated pulmonary artery pressure and increased pulmonary vascular resistance, ultimately leading to right heart failure. Early detection is critical for improving pa...

Cognitive impairment assessment using eye-tracking: multilevel saccade paradigms with differential analysis and attention-based neural networks.

Physiological measurement
. The accurate assessment of cognitive impairment plays a vital role in more targeted treatments for Dementia. Eye movement analysis is a non-invasive and objective method that offers fine-grained insight into cognitive functioning, complementing con...

Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting.

Emergency medicine journal : EMJ
BACKGROUND: Early intervention in patients with major traumatic injuries is critical. Decision support can improve clinicians' ability to identify high-risk patients. The aim of this study was to compare the performance of a machine-learning (ML) dec...

Voice clones sound realistic but not (yet) hyperrealistic.

PloS one
AI-generated voices are increasingly prevalent in our lives, via virtual assistants, automated customer service, and voice-overs. With increased availability and affordability of AI-generated voices, we need to examine how humans perceive them. Recen...

Prediction of biological age using machine learning.

PloS one
In response to Taiwan's rapidly aging population and the rising demand for personalized health care, accurately assessing individual physiological aging has become an essential area of study. This research utilizes health examination data to propose ...

Defining individualized theta frequency for memory modulation: A machine learning approach across brain states and regions.

NeuroImage
Recent transcranial alternating current stimulation (tACS) studies suggest that theta-frequency stimulation can modulate memory performance, with evidence highlighting individual variability in optimal stimulation frequency. However, it remains uncle...

Comparative evaluation of traditional and AI-based intraocular lens power calculation formulas in highly myopic eyes.

BMC ophthalmology
PURPOSE: To assess the accuracy of artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas compared with traditional methods in highly myopic eyes, and to evaluate their performance across varying axial lengths and cornea...