INTRODUCTION AND OBJECTIVE: Urosymphyseal fistula (UF) with osteomyelitis most commonly occurs as a result of prostate cancer and benign prostate hyperplasia therapy. UF presentation typically includes debilitating pelvic pain exacerbated with ambula...
Physiologically based pharmacokinetic (PBPK) modeling has the potential to play significant roles in estimating internal chemical exposures. The three major PBPK model input parameters (i.e., absorption rate constants, volumes of the systemic circula...
Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
Nov 2, 2021
BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implantation. This study aimed to set up and validate a deep learning algorithm to predict corneal back surf...
BACKGROUND: Advancements based on artificial intelligence have emerged in all areas of medicine. Many decisions in organ transplantation can now potentially be addressed in a more precise manner with the aid of artificial intelligence.
Developing a convolutional neural network (CNN) for medical image segmentation is a complex task, especially when dealing with the limited number of available labelled medical images and computational resources. This task can be even more difficult i...
Machine learning (ML) is a computerized analytical technique that is being increasingly employed in biomedicine. ML often provides an advantage over explicitly programmed strategies in the analysis of multidimensional information by recognizing relat...
In the era of data-driven medicine, rapid access and accurate interpretation of medical images are becoming increasingly important. The DICOM Image ANalysis and Archive (DIANA) system is an open-source, lightweight, and scalable Python interface that...
: Determining the presence or absence of cochlear dead regions (DRs) is essential in clinical practice. This study proposes a machine learning (ML)-based model that applies oversampling techniques for predicting DRs in patients. : We used recursive p...
In healthcare, a multitude of data is collected from medical sensors and devices, such as X-ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that can be analyzed by artificial intelligence methods for early diagnosis of ...
Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as ex...
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