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Deep learning enables genetic analysis of the human thoracic aorta.

Nature genetics
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance i...

Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19.

Scientific reports
A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing historic...

Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

Scientific reports
We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models ...

Ureteroileal anastomosis stricture after urinary diversions performed by open, laparoscopic and robotic approaches. Incidence and management in a tertiary care center.

Actas urologicas espanolas
INTRODUCTION: Ureteroileal anastomosis stricture is a frequent complication after radical cystectomy and ileal conduit or orthotopic neobladder formation. We analyze their incidence based on the technique for urinary diversion and on the surgical app...

Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study.

BMC medical imaging
BACKGROUND: Tc-pertechnetate thyroid scintigraphy is a valid complementary avenue for evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively simple but the interpretation still has a moderate consistency among...

Artificial Intelligence Algorithm-Based Analysis of Ultrasonic Imaging Features for Diagnosis of Pregnancy Complicated with Brain Tumor.

Journal of healthcare engineering
This research was to explore the accuracy of ultrasonic diagnosis based on artificial intelligence algorithm in the diagnosis of pregnancy complicated with brain tumors. In this study, 18 patients with pregnancy complicated with brain tumor confirmed...

Artificial intelligence modelling in differentiating core biopsies of fibroadenoma from phyllodes tumor.

Laboratory investigation; a journal of technical methods and pathology
Breast fibroepithelial lesions (FEL) are biphasic tumors which consist of benign fibroadenomas (FAs) and the rarer phyllodes tumors (PTs). FAs and PTs have overlapping features, but have different clinical management, which makes correct core biopsy ...

Artificial neural network model effectively estimates muscle and fat mass using simple demographic and anthropometric measures.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Lean muscle and fat mass in the human body are important indicators of the risk of cardiovascular and metabolic diseases. Techniques such as dual-energy X-ray absorptiometry (DXA) accurately measure body composition, but they are c...