ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low-and high-grade glioma patients-manually annotated by up to four raters-and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.
Top Ten Tips Palliative Care Clinicians Should Know About Caring for Chinese American Patients

The Chinese American population is one of the fastest-growing communities in the United States, composed of ∼5.4 million people, and represents ∼5.5% of overseas Chinese populations. With an expected exponential population rise, Chinese American patients who experience serious illness or approach end-of-life (EOL) may find their cultural values influencing the medical care they receive. Palliative care clinicians must recognize diverse cultural beliefs and preferences of Chinese American patients and their families. In this study, we provide 10 cultural pearls to guide the provision of palliative and EOL care for Chinese American patients, including discussions of Chinese traditions, communication strategies for Chinese patients and families, advance care planning, and EOL care beliefs.
Fuzzy-ART based adaptive digital watermarking scheme

In this paper, a novel transform domain digital watermarking scheme that uses visually meaningful binary image as watermark has been developed. The method embeds the watermark information adaptively with localized embedding strength according to the noise sensitivity level of the host image. Fuzzy adaptive resonance theory (Fuzzy-ART) classification is used to identify appropriate locations for watermark insertion and its control parameters add agility to the clustering results to thwart counterfeiting attacks. The scalability of visually recognizable watermark is exploited to devise a robust weighted recovery method with composite watermark. The proposed watermarking schemes can also be employed for oblivious detection. Unlike most oblivious watermarking schemes, our methods allow the use of visually meaningful image as watermark. For automation friendly verification, a normalized correlation metric that suits well with the statistical property of our methods is used. The experimental results show that the proposed techniques can survive several kinds of image processing attacks and the JPEG lossy compression.
Pruning strategies for mining high utility itemsets

High utility itemset mining problem involves the use of internal and external utilities of items (such as profits, margins) to discover interesting patterns from a given transactional database. It is an extension of the basic frequent itemset mining problem and is proven to be considerably hard and intractable. This is due to the lack of inherent structural properties of high utility itemsets that can be exploited. Several heuristic methods have been suggested in the literature to limit the large search space. This paper aims to improve the state-of-the-art and proposes a high utility mining method that employs novel pruning strategies. The utility of the proposed method is demonstrated through rigorous experimentation on several real and synthetic benchmark sparse and dense datasets. A comparative evaluation of the method against a state-of-the-art method is also presented. Our experimental results reveal that the proposed method is very effective in pruning unpromising candidates, especially for sparse transactional databases. (C) 2014 Elsevier Ltd. All rights reserved.
Design considerations of channel buffer amplifiers for low-power area-efficient column drivers in active-matrix LCDs

The performance criteria and corresponding design specifications for channel buffer amplifiers in state-of-the-art column driver ICs of active-matrix LCD (AMLCD) applications are presented. And the relationships between the amplifier characteristics and the display image quality are defined. In addition, several display patterns and their driving waveforms that enable the prediction of the performance of channel buffer amplifiers in real panel applications are presented(1).
Superpixel Hierarchy

Superpixel segmentation has been one of the most important tasks in computer vision. In practice, an object can be represented by a number of segments at finer levels with consistent details or included in a surrounding region at coarser levels. Thus, a superpixel segmentation hierarchy is of great importance for applications that require different levels of image details. However, there is no method that can generate all scales of superpixels accurately in real time. In this paper, we propose the superhierarchy algorithm which is able to generate multiscale superpixels as accurately as the state-of-the-art methods but with one to two orders of magnitude speed-up. The proposed algorithm can be directly integrated with recent efficient edge detectors to significantly outperform the state-of-the-art methods in terms of segmentation accuracy. Quantitative and qualitative evaluations on a number of applications demonstrate that the proposed algorithm is accurate and efficient in generating a hierarchy of superpixels.
Comprehensive Assessment of Coronary Calcification in Intravascular OCT Using a Spatial-Temporal Encoder-Decoder Network

Coronary calcification is a strong indicator of coronary artery disease and a key determinant of the outcome of percutaneous coronary intervention. We propose a fully automated method to segment and quantify coronary calcification in intravascular OCT (IVOCT) images based on convolutional neural networks (CNN). All possible calcified plaques were segmented from IVOCT pullbacks using a spatial-temporal encoder-decoder network by exploiting the 3D continuity information of the plaques, which were then screened and classified by a DenseNet network to reduce false positives. A novel data augmentation method based on the IVOCT image acquisition pattern was also proposed to improve the performance and robustness of the segmentation. Clinically relevant metrics including calcification area, depth, angle, thickness, volume, and stent-deployment calcification score, were automatically computed. 13844 IVOCT images with 2627 calcification slices from 45 clinical OCT pullbacks were collected and used to train and test the model. The proposed method performed significantly better than existing state-of-the-art 2D and 3D CNN methods. The data augmentation method improved the Dice similarity coefficient for calcification segmentation from 0.615 +/- 0.332 to 0.756 +/- 0.222, reaching human-level inter-observer agreement. Our proposed region-based classifier improved image-level calcification classification precision and F1-score from 0.725 +/- 0.071 and 0.791 +/- 0.041 to 0.964 +/- 0.002 and 0.883 +/- 0.008, respectively. Bland-Altman analysis showed close agreement between manual and automatic calcification measurements. Our proposed method is valuable for automated assessment of coronary calcification lesions and in-procedure planning of stent deployment.
Generation of Anatomically Inspired Human Airway Tree Using Electrical Impedance Tomography: A Method to Estimate Regional Lung Filling Characteristics

The purpose of lung recruitment is to improve and optimize the air exchange flow in the lungs by adjusting the respiratory settings during mechanical ventilation. Electrical impedance tomography (EIT) is a monitoring tool that permits measurement of regional pulmonary filling characteristics or filling index (FI) during ventilation. The conventional EIT system has limitations which compromise the accuracy of the FI. This paper proposes a novel and automated methodology for accurate FI estimation based on EIT images of recruitable regional collapse and hyperdistension during incremental positive end-expiratory pressure. It identifies details of the airway tree (AT) to generate a correction factor to the FIs providing an accurate measurement. Multi-scale image enhancement followed by identification of the AT skeleton with a robust and self-exploratory tracing algorithm is used to automatically estimate the FI. AT tracing was validated using phantom data on a ground-truth lung. Based on generated phantom EIT images, including an established reference, the proposed method results in more accurate FI estimation of 65% in all quadrants compared with the current state-of-the-art. Measured regional filling characteristics were also examined by comparing regional and global impedance variations in clinically recorded data from ten different subjects. Clinical tests on filling characteristics based on extraction of the AT from the resolution enhanced EIT images indicated a more accurate result compared with the standard EIT images.
Enzymatic Late-Stage Halogenation of Peptides

The late-stage site-selective derivatisation of peptides has many potential applications in structure-activity relationship studies and postsynthetic modification or conjugation of bioactive compounds. The development of orthogonal methods for C-H functionalisation is crucial for such peptide derivatisation. Among them, biocatalytic methods are increasingly attracting attention. Tryptophan halogenases emerged as valuable catalysts to functionalise tryptophan (Trp), while direct enzyme-catalysed halogenation of synthetic peptides is yet unprecedented. Here, it is reported that the Trp 6-halogenase Thal accepts a wide range of amides and peptides containing a Trp moiety. Increasing the sequence length and reaction optimisation made bromination of pentapeptides feasible with good turnovers and a broad sequence scope, while regioselectivity turned out to be sequence dependent. Comparison of X-ray single crystal structures of Thal in complex with d-Trp and a dipeptide revealed a significantly altered binding mode for the peptide. The viability of this bioorthogonal approach was exemplified by halogenation of a cyclic RGD peptide.
Magnetotransport in Graphene/Pb0.24Sn0.76Te Heterostructures: Finding a Way to Avoid Catastrophe

While heterostructures are ubiquitous tools enabling new physics and device functionalities, the palette of available materials has never been richer. Combinations of two emerging material classes, two-dimensional materials and topological materials, are particularly promising because of the wide range of possible permutations that are easily accessible. Individually, both graphene and Pb1-xSnxTe (PST) are widely investigated for spintronic applications because graphene's high carrier mobility and PST's topologically protected surface states are attractive platforms for spin transport. Here, we combine monolayer graphene with PST and demonstrate a hybrid system with properties enhanced relative to the constituent parts. Using magnetotransport measurements, we find carrier mobilities up to 20 000 cm2/(V s) and a magnetoresistance approaching 100%, greater than either material prior to stacking. We also establish that there are two distinct transport channels and determine a lower bound on the spin relaxation time of 4.5 ps. The results can be explained using the polar catastrophe model, whereby a high mobility interface state results from a reconfiguration of charge due to a polar/nonpolar interface interaction. Our results suggest that proximity induced interface states with hybrid properties can be added to the still growing list of behaviors in these materials.
Risk of venous thromboembolism during the use of oral estrogen-progestogen hormone therapies in light of most recent research findings

Two important studies evaluating the safety profile of oral estrogen-progestogen hormonal therapies conducted in standard clinical practice with respect to the venous system were recently published. A large prospective controlled cohort study (PRO-E2) based on the non-inferiority design has shown that the relative risk of developing venous thrombosis (VTE) in women using combined oral hormonal contraceptives (COHC) containing 17β-estradiol (1.5 mg) and nomegestrol acetate (2.5 mg) (E2/NOMAC) was not statistically different from that in users of COHC containing ethinylestradiol and levonorgestrel (EE/LNG). The aim of the recently presented study was to compare the risk of VTE in patients treated with a product for oral continuous combined menopausal hormone therapy containing 1 mg of 17ß-estradiol and 100 mg of micronized progesterone (1 mgE2/100 mgP4) with patients taking conjugated equine estrogens and medroxyprogesterone acetate (CEE/MPA). The study was based on an analysis of records retrieved from a US health insurance database, and was therefore concerned the real-life clinical practice. The hazard ratio of VTE when comparing 1 mgE2/100 mgP4 with CEE/MPA was 0.70 (95% CI: 0.53-0.92). The difference was found to be statistically significant (p < 0.05). The rewieved studies provide further evidence that the use of hormones bioidentical with endogenous steroids in oral contraception and menopausal hormone therapy creates an opportunity to combine high efficacy with a favorable safety profile.
[Establishment of Evaluation System for Medical Optical Radiation Protective Eyewears]

As a kind of class II medical device, medical optical radiation protective eyewears should meet the requirements of safety and effectiveness. In this study, the evaluation system of medical optical radiation protective eyewears is established. Combined with the medical device registration unit division guidelines, the classification method of medical optical radiation protective eyewears is given. Medical optical radiation protective eyewears are not only assembled spectacles, but also have special optical radiation protection performance. The performance evaluation method of medical optical radiation protective eyewears and the evaluation method of shelf life for medical optical radiation protective eyewears are given.
Characterization of the Individual Short-Term Frequency Stability of Cryogenic Sapphire Oscillators at the 10(-16) Level

We present the characterization of three cryogenic sapphire oscillators (CSOs) using the three-cornered-hat method. Easily implemented with commercial components and instruments, this method reveals itself very useful to analyze the fractional frequency stability limitations of these state-of-the-art ultrastable oscillators. The best unit presents a fractional frequency stability better than 5 x 10(-16) at 1 s and below 2 x 10(-16) for tau < 5000 s.
Improving the Computational Cost of Image Reconstruction in Biomedical Magnetic Induction Tomography Using a Volume Integral Equation Approach

Magnetic induction tomography is a novel imaging method with promising biomedical applications. The image reconstruction problem suffers from a high computation cost because of its inherent nonlinearity. Current state-of-the-art numerical methods are based on the finite element method (FEM). To avoid artifacts at the boundaries, this method requires the discretization of a volume much larger than the actual volume of interest. A numerical model based on volume integrals only requires the discretization of the volume of interest, which greatly reduces the number of unknowns. Fewer unknowns generally imply a lower computation cost. However, a naive implementation of the volume integral equation does not yield a lower computation cost due to the bad conditioning arising from the high dielectric property values of biological tissues at low frequencies. To tackle this problem, a model based on inhomogeneous Green's function is proposed. The forward model is validated with the Mie scattering theory. Through the resolution of the inverse problem, it is found that the reconstruction limits compare well with current state-of-the-art methods. By reducing the number of unknowns and maintaining a similar computational complexity, the proposed model offers a computation cost reduction when compared with the FEM.
Art Meets Sport: What Can Actor Training Bring to Physical Literacy Programs?

The aim of this communication is to highlight synergies and opportunities between the fields of education, sport and health and the performing arts for the promotion of physical literacy. First, physical literacy is introduced and then defined according to the definition used in this communication. Secondly, we highlight the gap in physical literacy interventions, in that they do not address learning based on a holistic comprehensive definition of physical literacy. Then we provide examples of interventions that do borrow from the arts, such as circus arts, and show how these approaches explicitly link to the discipline of arts. This is followed by program examples, which approach motor and language development from discipline-specific perspectives. Then we introduce actor training (within the discipline of arts) in terms of how this approach may be useful to our understanding of physical literacy and how to expand the conception of physical literacy to include affective meaning making, and tolerance for ambiguity and discomfort in not-knowing. Finally, we conclude with the next step for the bridging of disciplines in order to further our journey to understand and improve physical literacy.
Enantiopure β-isocyano-boronic esters: synthesis and exploitation in isocyanide-based multicomponent reactions

Various boron-containing isocyanides have been efficiently synthesized from the corresponding enantiopure β-substituted β-amino boronic acid pinacol esters, without need for protecting group interconversion, through a two-step, purification-free procedure. They were employed in a variety of isocyanide-based multicomponent reactions, proving to be reliable components for all of them and allowing the efficient synthesis of unprecedented, boron-containing peptidomimetics and heteroatom-rich small molecules, including biologically relevant cyclic boronates. Jointing together the β-amido boronic acid moiety, deriving from the isocyanide component, with prominent pharmacophoric rings emerging from the multicomponent process, a successful application of the molecular hybridization concept could be realized.
Orphan Medical Devices and Pediatric Cardiology - What Interventionists in Europe Need to Know, and What Needs to be Done

Medical devices include a great diversity of technologies, which are evaluated and approved in the European Union (EU) according to a revised law that came into effect on 26 May 2021, known as the Medical Device Regulation or MDR (EU 745/2017). It has a transition period that allows products that were approved under the previous rules (the EU Medical Device Directives) to continue to be marketed until 26 May 2024 at the latest. As a result of a series of unforeseen factors, there is a possibility that the MDR may result in products becoming unavailable, with the consequent risk of a loss of some interventions that are reliant upon those devices. Devices that are used for orphan or pediatric indications are particularly vulnerable to this. There is an urgent need for policy to be developed to protect essential medical devices for orphan indications and for use in children, to ensure that necessary interventions can continue, and to ensure a more sustainable system in Europe over the longer term. Pediatric cardiologists in Europe need to be aware that particular medical devices may become unavailable over the next two years, and they should contribute to plans to mitigate this risk, so that they can continue to deliver the best possible care for their patients. This commentary examines the factors which have contributed to this issue and suggests ways that policy can be developed to address it.Article title: Kindly check and confirm the edit made in the title.Title is okay.
Innate and Peripheral Immune Alterations after Traumatic Brain Injury Are Regulated in a Gut Microbiota-Dependent Manner in Mice

Traumatic brain injury (TBI) patients are at high risk for disruption of the gut microbiome. Previously, we have demonstrated that broad-spectrum antibiotic exposure after TBI drastically alters the gut microbiota and modulates neuroinflammation, neurogenesis, and long-term fear memory. However, these data did not determine if the impact of antibiotic exposure on the brain's response to injury was mediated directly by antibiotics or indirectly via modulation of the gut microbiota. We designed two different approaches to address this knowledge gap. One was utilizing fecal microbiota transplantation (FMT) from control and antibiotic-treated mice (treated with vancomycin, neomycin, ampicillin, and metronidazole [VNAM]) into germ-free (GF) mice prior to injury, and the other was exposing specific pathogen-free (SPF) mice to a 2-week period of antibiotics prior to injury but discontinuing antibiotics 72 h prior to injury. GF mice receiving FMT from VNAM-treated mice (GF-VNAM) demonstrated reduced gut bacterial alpha diversity and richness compared with GF mice receiving control FMT. At 7 days post-injury, GF-VNAM had increased microglial activation, reduced infiltration of T cells, and decreased neurogenesis. Similarly, SPF mice exposed to antibiotics prior to but not after injury demonstrated similar alterations in neuroinflammation and neurogenesis compared with control mice. These data support our hypothesis implicating the gut microbiota as an important modulator of the neuroinflammatory process and neurogenesis after TBI and provide an exciting new approach for neuroprotective therapeutics for TBI.
Using multiple spatio-temporal features to estimate video quality

In this paper, we propose a new video quality metric based on a set of multiple features that incorporate texture, saliency, spatial activity, and temporal attributes. A random forest regression algorithm is used to combine these features and obtain a video quality score. Experimental results show that the proposed metric has a good performance when tested on several benchmark video quality databases, outperforming current state-of-the-art full-reference video quality metrics.