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High numbers of consumable medical materials (eg, sterile needles and swabs) are used during the daily routine of intensive care units (ICUs) worldwide. Although medical consumables largely contribute to total ICU hospital expenditure, many hospitals do not track the individual use of materials. Current tracking solutions meeting the specific requirements of the medical environment, like barcodes or radio frequency identification, require specialized material preparation and high infrastructure investment. This impedes the accurate prediction of consumption, leads to high storage maintenance costs caused by large inventories, and hinders scientific work due to inaccurate documentation. Thus, new cost-effective and contactless methods for object detection are urgently needed.
This article was published in the following journal.
Name: JMIR medical informatics
Deep-learning has the potential to assist the medical diagnostic process. We aimed to identify facial anomalies associated with endocrinal disorders using a deep-learning approach to facilitate the pr...
A deep learning approach has been taken to improve detection characteristics of surface plasmon microscopy (SPM) of light scattering. Deep learning based on convolutional neural network algorithm was ...
Aim & Scope: Artificial intelligence (AI) in medicine is a fast-growing field. The rise of deep learning algorithms, such as convolutional neural networks (CNNs), offers fascinating perspectives for t...
In this paper, we describe a new approach to generating standardized e-Learning content from existing medical collections. The core of this approach is a tool called Clavy, which makes it possible to ...
To improve the performance of Intensive Care Units (ICUs), the field of bio-statistics has developed scores which try to predict the likelihood of negative outcomes. These help evaluate the effectiven...
An association study with large database from electronic medical record system, images, outcome analysis and genetic single nucleotide polymorphism variations by machine learning and artif...
CT-guided epidural steroid injection (ESI) thrives among interventional radiologists. Although X-ray fluoroscopy still remains as the gold standard to guide ESI, CT guidance has the merits...
Lung cancer diagnosis and staging are two fundamental and critical issue in clinical lung cancer management and therapeutic decision-making. Invasive procedures for pathologic analysis are...
A key element in the diagnosis of non-alcoholic fatty liver disease (NAFLD) is the differentiation of non-alcoholic steatohepatitis (NASH) from non-alcoholic fatty liver (NAFL) and the sta...
The aim of this study is to test an intervention that has potential to improve acute care skills and confidence related to safe delivery and newborn care for mid-level health providers in ...
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
Any situation where an animal or human is trained to respond differentially to two stimuli (e.g., approach and avoidance) under reward and punishment conditions and subsequently trained under reversed reward values (i.e., the approach which was previously rewarded is punished and vice versa).
Individuals professionally qualified in the management of patients' records. Duties may include planning, designing, and managing systems for patient administrative and clinical data, as well as patient medical records. The concept includes medical record technicians.
The absence of a useful purpose or useful result in a diagnostic procedure or therapeutic intervention. The situation of a patient whose condition will not be improved by treatment or instances in which treatment preserves permanent unconsciousness or cannot end dependence on intensive medical care. (From Ann Intern Med 1990 Jun 15;112(12):949)
Works providing an analytical subject approach to materials in a field of knowledge.