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Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence.

Computers in biology and medicine
BACKGROUND: In intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS-2), though commonly used, relies heavily on comprehensive cl...

Deep learning-based prediction of in-hospital mortality for sepsis.

Scientific reports
As a serious blood infection disease, sepsis is characterized by a high mortality risk and many complications. Accurate assessment of mortality risk of patients with sepsis can help physicians in Intensive Care Unit make optimal clinical decisions, w...

Cystic renal mass screening: machine-learning-based radiomics on unenhanced computed tomography.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: The present study compares the diagnostic performance of unenhanced computed tomography (CT) radiomics-based machine learning (ML) classifiers and a radiologist in cystic renal masses (CRMs).

Link prediction based on spectral analysis.

PloS one
Link prediction in complex network is an important issue in network science. Recently, various structure-based similarity methods have been proposed. Most of algorithms are used to analyze the topology of the network, and to judge whether there is an...

The correlation between serum creatinine and burn severity and its predictive value.

Cellular and molecular biology (Noisy-le-Grand, France)
This study aimed to explore the correlation between serum creatinine and burn severity and the value of predicting the outcome of patients. For this purpose, a total of 268 burn patients (BUP) were collected. According to the burn area, they were div...

Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning.

Journal of cancer research and therapeutics
PURPOSE: To evaluate the capability of deep transfer learning (DTL) and fine-tuning methods in differentiating malignant from benign lesions in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Treatment prediction with machine learning in prostate cancer patients.

Computer methods in biomechanics and biomedical engineering
There are various treatment modalities for prostate cancer, which has a high incidence. In this study, it is aimed to make predictions with machine learning in order to determine the optimal treatment option for prostate cancer patients. The study in...

A Deep Learning Model for Detecting Rhegmatogenous Retinal Detachment Using Ophthalmologic Ultrasound Images.

Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde
INTRODUCTION: Rhegmatogenous retinal detachment (RRD) is one of the most common fundus diseases. Many rural areas of China have few ophthalmologists, and ophthalmologic ultrasound examination is of great significance for remote diagnosis of RRD. Ther...

Deep learning for classifying the stages of periodontitis on dental images: a systematic review and meta-analysis.

BMC oral health
BACKGROUND: The development of deep learning (DL) algorithms for use in dentistry is an emerging trend. Periodontitis is one of the most prevalent oral diseases, which has a notable impact on the life quality of patients. Therefore, it is crucial to ...

Hessian Regularized -Nonnegative Matrix Factorization and Deep Learning for miRNA-Disease Associations Prediction.

Interdisciplinary sciences, computational life sciences
Since the identification of microRNAs (miRNAs), empirical research has demonstrated their crucial involvement in the functioning of organisms. Investigating miRNAs significantly bolsters efforts related to averting, diagnosing, and treating intricate...