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Background: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text such as electronic health record (EHR) notes. This opens the door to large‐scale projects that rely on variables that are not typically recorded in a structured form, such as patient signs and symptoms. Objectives: This study is designed to acquaint the emergency medicine research community with the foundational elements of NLP, highlighting essential terminology, annotation methodologies, and the intricacies involved in training and evaluating NLP models. Symptom characterization is critical to urinary tract infection (UTI) diagnosis, but identification of symptoms from the EHR has historically been challenging, limiting large‐scale research, public health surveillance, and EHR‐based clinical decision support. We therefore developed and compared two NLP models to identify UTI symptoms from unstructured emergency department (ED) notes. Methods: The study population consisted of patients aged ≥ 18 who presented to an ED in a northeastern U.S. health system between June 2013 and August 2021 and had a urinalysis performed. We annotated a random subset of 1250 ED clinician notes from these visits for a list of 17 UTI symptoms. We then developed two task‐specific LLMs to perform the task of named entity recognition: a convolutional neural network‐based model (SpaCy) and a transformer‐based model designed to process longer documents (Clinical Longformer). Models were trained on 1000 notes and tested on a holdout set of 250 notes. We compared model performance (precision, recall, F1 measure) at identifying the presence or absence of UTI symptoms at the note level. Results: A total of 8135 entities were identified in 1250 notes; 83.6% of notes included at least one entity. Overall F1 measure for note‐level symptom identification weighted by entity frequency was 0.84 for the SpaCy model and 0.88 for the Longformer model. F1 measure for identifying presence or absence of any UTI symptom in a clinical note was 0.96 (232/250 correctly classified) for the SpaCy model and 0.98 (240/250 correctly classified) for the Longformer model. Conclusions: The study demonstrated the utility of LLMs and transformer‐based models in particular for extracting UTI symptoms from unstructured ED clinical notes; models were highly accurate for detecting the presence or absence of any UTI symptom on the note level, with variable performance for individual symptoms. [ABSTRACT FROM AUTHOR]

The first involved COVERAGE Data Viewer that integrates ISS on the back-end for interactive subsetting of selected in situ data layers available via the visualization tool. The COVERAGE Data Viewer is based on JPL's Open Source Common Mapping Client (CMC) Software framework (https://coverage.ceos.org/cmc/) and provides a well-rounded visualization capability for ocean data. [Extracted from the article]

BRCAness is considered a predictive biomarker to platinum and poly(ADP‐ribose) polymerase (PARP) inhibitors. However, recent trials showed that its predictive value was limited in triple‐negative breast cancer (TNBC) treated with platinum. Moreover, tumors with mutations of DNA damage response (DDR) genes, such as homologous recombination (HR) genes, could be sensitive to platinum and PARP inhibitors. Thus, we aim to explore the relationship between mutation status of DDR genes and BRCAness in TNBC. We sequenced 56 DDR genes in 120 TNBC and identified BRCAness by array comparative genomic hybridization. The sequencing results showed that 13, 14, and 14 patients had BRCA, non‐BRCA HR, and non‐HR DDR gene mutations, respectively. Array comparative genomic hybridization revealed that BRCA‐mutated and HR gene‐mutated TNBC shared similar BRCAness features, both having higher numbers and longer length of large‐scale structural aberration (LSA, >10 Mb) and similar altered chromosomal regions of LSA. These suggested non‐BRCA HR gene‐mutated TNBC shared similar characteristics with BRCA‐mutated TNBC, indicating non‐BRCA HR gene‐mutated TNBC sensitive to platinum and PARP inhibitors. Among tumors with mutation of non‐HR DDR genes, 3 PTEN and 1 MSH6 mutation also contained significant LSAs (BRCAness); however, they had different regions of genomic alteration to BRCA and HR gene‐mutated tumors, might explain prior findings that PTEN‐ and MSH6‐mutated cancer cells not sensitive to PARP inhibitors. Therefore, we hypothesize that the heterogeneous genomic background of BRCAness indicates different responsiveness to platinum and PARP inhibitors. Direct sequencing DDR genes in TNBC should be applied to predict their sensitivity toward platinum and PARP inhibitors. [ABSTRACT FROM AUTHOR]

The formation of the tropylium ion, C7H7+, in the mass spectrum of toluene is a chemical process that has been extensively studied. There is, however, still debate as to the structure of the moieties and the reaction pathways involved. This work presents the first computationally complete reaction schemes for the formation of tropylium from toluene to be reported. The calculations were performed at the HF/6-31G(d, p) and the DFT/B3LYP/6-311++G(2d) levels of theory using Gaussian 03W. The previously unreported optimized structures and energies for a transition state and an intermediate in one scheme and a transition state in the other have been determined. These results are consistent with the previously reported literature and the available experimental data. © 2009 Wiley Periodicals, Inc. Int J Quantum Chem, 2009 [ABSTRACT FROM AUTHOR]

Purpose To evaluate high-resolution MRI of the triangular fibrocartilage complex (TFCC) at 3T using a surface coil (SC) or volume coil (VC). Materials and Methods MRI was obtained from nine volunteers in the supine position with a 3-inch SC and in prone position with a transmit-receiver wrist VC at 3T. Coronal two-dimensional-gradient echo (2D-GRE) images (TR/TE/FA = 500 msec/15 msec/40°, 1 mm slice-thickness, 60 mm field of view [FOV], 192 × 256 matrix) and coronal 3D-GRE images (TR/TE/FA = 33 msec/15 msec/10°, 0.8 mm slice-thickness, 80 mm FOV, 256 × 256 matrix) were used. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the TFCC and surrounding structures were measured. For qualitative measurement, visualization of TFCC and intercarpal ligaments was graded. Results SNR of TFCC, cartilage, and bone marrow on 2D-GRE with SC/VC was as follows: 5.3/5.3 (TFCC), 16.5/14.4 (cartilage), and 3.61/3.96 (bone marrow). 3D-GRE showed similar SNR. Cartilage-TFCC/cartilage-bone marrow CNR were 11.1/12.8 (SC-2D-GRE), 8.8/10.5 (VC-2D-GRE), 14.1/15.5 (SC-3D-GRE), and 11.9/15.0 (VC-3D-GRE). Quantitative values were not significantly different between SC and VC. Visualization of TFCC and intercarpal ligament with SC was superior to that with VC. All structures show higher scores with 3D-GRE imaging compared to 2D-GRE imaging. Conclusion SC may provide superior qualitative and quantitative results and can be an alternative in case of difficulty in prone position at 3T. J. Magn. Reson. Imaging 2007;26:701-707. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Infrared spectrometry has correlated excellently with mass spectrometry in detecting the ratio of 13CO2 to 12CO2 in breath samples. The present study aimed to evaluate the accuracy of the 13C-urea breath test (13C-UBT) using a new model of infrared analyzer. A total of 600 patients who were undergoing upper endoscopy without receiving eradication therapy were entered into the study. Culture, histology, and rapid urease test on biopsies from the antrum and corpus of the stomach were used for the determination of Helicobacter pylori infection . Breath samples were collected before and 20 min after drinking 100 mg 13C-urea in 100 mL water. The optimal cutoff value was determined by the receiver operating characteristic curve. Of the 586 patients who were eligible for analysis, 369 were positive for H. pylori infection, 185 were negative for H. pylori infection, and 32 were indeterminate. When the appropriate cutoff value was set at 3.5‰, a sensitivity of 97.8%, a specificity of 96.8% and an accuracy of 97.5% were obtained using the 13C-UBT. The accuracy of the 13C-UBT decreased when CO2 concentration in the breath sample was <2%, as compared with ≥2% (93.6% vs 97.7%), mainly because of a decrease in specificity (81.8% vs 97.7%). There were 2.7% of patients with Δ13CO2 values that fell between 3.0–4.5‰, in whom the risk of error was 47%. The 13C-UBT performed with infrared spectrometry is a highly sensitive, specific, and non-invasive method for the detection of H. pylori infection. The immediate availability of the test result and technical simplicity make it particularly effective in routine clinical practice. [ABSTRACT FROM AUTHOR]

In this article, a new video coding system is proposed which takes advantage of both intrascale and interscale similarities present in video sequences. Each block in every frame is approximated with a linear combination of members of an adaptive library of blocks constructed for that block. This library is made up of some fixed blocks (e.g., DCT basis blocks) and some adaptive blocks. The adaptive library blocks are blocks of the same size or larger blocks that are shrunk, taken from the previous frame. For each block in every frame, a rate-distortion optimized fully orthogonal matching pursuit algorithm is used to determine how many and which ones of the members of the library constructed for that block should be selected and linearly combined to approximate the block most efficiently in terms of bit rate and rms error. Simulation results on sample gray-scale video sequence “Miss America” suggests that this method has promising coding performance in terms of PSNR and bit rate,especially compared to other published fractal-based video compression methods. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 305–319, 1998 [ABSTRACT FROM AUTHOR]

We propose a motion estimation system that uses stereo image pairs as the input data. To perform experimental work, we also obtain a sequence of outdoor stereo images taken by two metric cameras. The system consists of four main stages, which are (1) determination of point correspondences on the stereo images, (2) correction of distortions in image coordinates, (3) derivation of 3D point coordinates from 2D correspondences, and (4) estimation of motion parameters based on 3D point correspondences. For the first stage of the system, we use a four-way matching algorithm to obtain matched points on two stereo image pairs at two consecutive brae instants (t, and t,.,). Since the input data are stereo images taken by cameras, it has two types of distortions, which are (i) film distortion and (ii) lens distortion. These two distortions must be corrected before any process can be applied on the matched points. To accomplish this goal, we use (i) bilinear transform for film distortion correction and (ii) lens formulas for lens distortion correction. After correcting the distortions, the results are 2D coordinates of each matched point that can be used to derive 3D coordinates. However, due to data noise, the calculated 3D coordinates do not usually represent a consistent rigid structure that is suitable for motion estimation; therefore, we suggest a procedure to select good 3D point sets as the input for motion estimation. The procedure exploits two constraints, rigidity between different time instants and uniform point distribution across the object on the image. For the last stage, we use an algorithm to estimate the motion parameters. We also wish to know what is the effect of quantization error on the estimated results; therefore an error analysis based on quantization error is performed on the estimated motion parameters. In order to test our system, eight sets of stereo image pairs are extracted from an outdoor stereo image sequence and used as the input data. The experimental results indicate that the proposed system does provide reasonable estimated motion parameters. [ABSTRACT FROM AUTHOR]

This article presents a model-based approach for nonrigid object motion and deformation analysis from 3D data. The modeling primitives used in this research are the superquadrics, which have already been proven useful in describing a variety of natural and man-made objects. This model-based approach is not only in accordance with the human visual perception process but also able to decouple the large and unstructured nonrigid motion estimation system into simple and well structured subsystems. We develop a recursive algorithm for estimating global motion and object shape, which effectively incorporates a priori knowledge of the object into the estimation procedure and obtains a good estimate of the global motion and object shape even if the given 3D points are distributed bias. After compensating for the global motion of the object, a tensor model of local deformation is introduced and a spherical harmonic surface-fitting algorithm is described such that the localized deformations of the object surface can be characterized. The local deformations of the object are then estimated using tensor-description-based analysis and parametrized by the directions and magnitudes of the extreme deformations in a localized surface element. To illustrate the potential of this model-based approach for nonrigid motion analysis, a real data example is presented using the proposed approach. This example involves estimating the left ventricle motion and deformations from a time sequence of 3D coordinates of coronary artery bifurcation points. The estimation results show the success of the model-based approach even when the given bifurcation points are distributed only on half of the left ventricle surface. [ABSTRACT FROM AUTHOR]

This paper describes a new algorithm which uses Gaussian and mean curvature values of the terrain surface to extract feature points. These points are then used for recognition of particular subregions of the terrain and in estimating relative positions of these subregions in the terrain. The Gaussian and mean curvatures are chosen because they are invariant under rotation and translation. In the Gaussian and mean curvature images, the points of maximum and minimum curvatures are extracted and used for matching. The stability of the position of these points in the presence of noise and with resampling is investigated. The input for this algorithm is 3D digital terrain data. Curvature values are calculated from the data by fitting a quadratic surface over a square window and calculating directional derivatives of this surface. A method of surface fitting that is invariant to sensor-centered coordinate system transformation is suggested and implemented. Real terrain data are used in our experiments. The algorithm is tested with and without the presence of noise, and its performance is described. [ABSTRACT FROM AUTHOR]

This article presents a robust algorithm for automated registration of images related by rigid-body transformations. This algorithm uses a new region-based similarity metric, which enables accurate registration of images of large contrast differences. Region segmentation required by the metric is accomplished using a multiscale segmentation algorithm, and minimization of this metric is done using the Powell direction set method. Experimental results are presented to demonstrate that the algorithm is effective for aligning images from single or multiple imaging modalities without the use of any fiducial markers. © 1997 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 8, 513–518, 1997 [ABSTRACT FROM AUTHOR]

We describe a curvature-based approach for estimating nonrigid motion of moving surfaces. We deal with conformal motion, which can be characterized by stretching of the surface. At each point, this stretching is equal in all directions but different for different points. The stretching function can be defined as additional (with global translation and rotation) motion parameter. We present a new algorithm for local stretching recovery from Gaussian curvature, based on polynomial (linear and quadratic) approximations of the stretching function. It requires point correspondences between time frames but not the complete knowledge of nonrigid transformation. Experiments on simulated and real data are performed to illustrate performance and accuracy of derived algorithms. Noise sensitivity of the algorithm is also evaluated using Gaussian noise on simulated data. [ABSTRACT FROM AUTHOR]

We explain that the task of multiple rigid motion segmentation and estimation from image feature point correspondences demands an estimator of high robustness. We show that a heuristics-based partial modeling approach can be used to develop a highly robust estimator called the MF estimator for general regression, where ‘MF’ represents an abbreviation of Model Fitting. Finally, we provide experimental results in estimating single rigid motion from a mixture of 2D-2D (or image-image), 3D-2D (or range-image), and 3D-3D (or range-range) corresponding point data by using the proposed MF estimator. As will be seen. only four well matched corresponding point pairs are needed to get a good estimate of motion parameters no matter how m(my mismatched corresponding point pairs (or outliers) occur. The article represents an initial effort towards robust image-motion analysis. [ABSTRACT FROM AUTHOR]

The estimation of the three-dimensional (3-D) motion parameters of a rigid body is a very important subject in scene analysis and trajectory prediction. Motion parameters can be estimated from two sets of object feature points before and after the motion In general, the matching correspondences of the feature points are available, and the motion parameters can be estimated by solving equations associated with the correspondences. In this paper, we present a new method for motion estimation from 3-D data without requiring the knowledge of matching correspondences. In the noise-free case. this approach identifies four candidates for the rotation matrix. The rotation matrix giving the best match of the point features can then be selected from the four candidates and the matching correspondences are subsequently established. Possible ambiguities due to symmetrical feature points are also discussed in this paper. In the presence of noise, this method provides an initial estimate of the motion, which is then used to establish the matching correspondences. Subsequently, a new estimate of the motion parameters can be obtained with the established matching correspondence information. The effects of random zero-mean noise are studied. Simulated results are shown to demonstrate the effectiveness and accuracy of this technique. [ABSTRACT FROM AUTHOR]

A new continuously tunable optoelectronic oscillator based on shifted dispersion‐induced RF‐fading is proposed and experimentally demonstrated. The design provides wideband continuously all‐optical tunability by incorporating the shifted RF‐fading based on a Mach‐Zehnder structure in an optoelectronic feedback loop. By simply varying the path difference between the two arms of the Mach‐Zehnder configuration via an adjustable variable delay line, the fundamental frequency of the oscillator can achieve extremely high and continuous tuning with a frequency upper bound dependent on the delay properties of the variable optical delay line. [ABSTRACT FROM AUTHOR]