AIMC Topic: Female

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The limits of fair medical imaging AI in real-world generalization.

Nature medicine
As artificial intelligence (AI) rapidly approaches human-level performance in medical imaging, it is crucial that it does not exacerbate or propagate healthcare disparities. Previous research established AI's capacity to infer demographic data from c...

Artificial Intelligence Methods for the Argenta Classification of Deformational Plagiocephaly to Predict Severity and Treatment Recommendation.

The Journal of craniofacial surgery
INTRODUCTION: Deformational plagiocephaly (DP) can be classified into 5 severity types using the Argenta scale (AS). Patients with type III or higher require referral to craniofacial surgery for management. Primary care pediatricians (PCPs) are often...

Machine learning for the prediction of delirium in elderly intensive care unit patients.

European geriatric medicine
PURPOSE: This study aims to develop and validate a prediction model for delirium in elderly ICU patients and help clinicians identify high-risk patients at the early stage.

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

Epilepsy research
BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is unc...

A deep learning approach for overall survival prediction in lung cancer with missing values.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevalent issue of missing data in the medical doma...

Non-invasive screening of bladder cancer using digital microfluidics and FLIM technology combined with deep learning.

Journal of biophotonics
Non-invasive screening for bladder cancer is crucial for treatment and postoperative follow-up. This study combines digital microfluidics (DMF) technology with fluorescence lifetime imaging microscopy (FLIM) for urine analysis and introduces a novel ...

Using machine learning to automatically measure kyphotic and lordotic angle measurements on radiographs for children with adolescent idiopathic scoliosis.

Medical engineering & physics
Measuring the kyphotic angle (KA) and lordotic angle (LA) on lateral radiographs is important to truly diagnose children with adolescent idiopathic scoliosis. However, it is a time-consuming process to measure the KA because the endplate of the upper...

Enhancing stroke risk and prognostic timeframe assessment with deep learning and a broad range of retinal biomarkers.

Artificial intelligence in medicine
Stroke stands as a major global health issue, causing high death and disability rates and significant social and economic burdens. The effectiveness of existing stroke risk assessment methods is questionable due to their use of inconsistent and varyi...

Enhanced choroid plexus segmentation with 3D UX-Net and its association with disease progression in multiple sclerosis.

Multiple sclerosis and related disorders
BACKGROUND: The choroid plexus (CP) is suggested to be closely associated with the neuroinflammation of multiple sclerosis (MS). Segmentation based on deep learning (DL) could facilitate rapid and reproducible volume assessment of the CP, which is cr...