AIMC Topic: Middle Aged

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Predictive models of clinical outcome of endovascular treatment for anterior circulation stroke using machine learning.

Journal of neuroscience methods
BACKGROUND AND PURPOSE: Mechanical Thrombectomy (MT) has recently become the standard of care for anterior circulation stroke with large vessel occlusion, but predictive factors of successful MT are still not clearly defined. To tailor treatment indi...

Deep Learning-Powered CT-Less Multitracer Organ Segmentation From PET Images: A Solution for Unreliable CT Segmentation in PET/CT Imaging.

Clinical nuclear medicine
PURPOSE: The common approach for organ segmentation in hybrid imaging relies on coregistered CT (CTAC) images. This method, however, presents several limitations in real clinical workflows where mismatch between PET and CT images are very common. Mor...

ProCUSNet: Prostate Cancer Detection on B-mode Transrectal Ultrasound Using Artificial Intelligence for Targeting During Prostate Biopsies.

European urology oncology
BACKGROUND AND OBJECTIVE: To assess whether conventional brightness-mode (B-mode) transrectal ultrasound images of the prostate reveal clinically significant cancers with the help of artificial intelligence methods.

Prediction of mortality in heart failure by machine learning. Comparison with statistical modeling.

European journal of internal medicine
BACKGROUND: Assessing the relative performance of machine learning (ML) methods and conventional statistical methods in predicting prognosis in heart failure (HF) still remains a challenging research field.

Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.

Computers in biology and medicine
This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require careful anticoagulation management. With rising rates of diabetes and cardiovascular diseases, understanding the factors influencing warfarin therapy...

Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.

World journal of surgical oncology
BACKGROUND: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperativ...

Identification of patient demographic, clinical, and SARS-CoV-2 genomic factors associated with severe COVID-19 using supervised machine learning: a retrospective multicenter study.

BMC infectious diseases
BACKGROUND: Drivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determinants and host-related factors (i.e., demographics, pre-existing conditions and/or genetics), thus ...

OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning.

Scientific reports
Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. T...