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David Beymer

David Beymer
IBM · Computer Science, Almaden

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114
Publications
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5,444
Citations

Publications

Publications (114)
Article
Full-text available
The COVID-19 pandemic has caused major disruptions to workplace safety and productivity. A browser-based interactive disease transmission simulation was developed to enable managers and individuals (agents) to optimize safe office work activities during pandemic conditions. The application provides a user interface to evaluate the impact of non-pha...
Preprint
Recently, there has been a growing availability of pre-trained text models on various model repositories. These models greatly reduce the cost of training new models from scratch as they can be fine-tuned for specific tasks or trained on large datasets. However, these datasets may not be publicly accessible due to the privacy, security, or intellec...
Preprint
With the unprecedented advancements in Large Language Models (LLMs), their application domains have expanded to include code generation tasks across various programming languages. While significant progress has been made in enhancing LLMs for popular programming languages, there exists a notable gap in comprehensive evaluation frameworks tailored f...
Preprint
Full-text available
Agent-based social simulation can be useful for creating digital twins of societies of interacting autonomous agents. Such simulations are useful for testing hypotheses about behaviour and belief change in the presence of interventions. In this paper, we introduce Clockwork, an efficient multi-agent simulation framework. The key contribution of thi...
Chapter
Artificial intelligence and in particular deep learning have shown great potential in the field of medical imaging. The models can be used to analyze radiology/pathology images to assist the physicians with their tasks in the clinical workflow such as disease detection, medical intervention, treatment planning, and prognosis to name a few. Accurate...
Chapter
Full-text available
The global COVID-19 pandemic has resulted in huge pressures on healthcare systems, with lung imaging, from chest radiographs (CXR) to computed tomography (CT) and ultrasound (US) of the thorax, playing an important role in the diagnosis and management of patients with coronavirus infection. The AI community reacted rapidly to the threat of the coro...
Article
Full-text available
[This corrects the article DOI: 10.1016/j.patter.2021.100269.].
Article
Full-text available
Although a plethora of research articles on AI methods on COVID-19 medical imaging are published, their clinical value remains unclear. We conducted the largest systematic review of the literature addressing the utility of AI in imaging for COVID-19 patient care. By keyword searches on PubMed and preprint servers throughout 2020, we identified 463...
Article
Full-text available
We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye-tracking system while a radiologist reviewed and reported on 1,083 CXR images. The dataset contains the following aligned data: CXR image, transcribed radiology report text, radiologist’s dictation audio a...
Preprint
Full-text available
The global COVID-19 pandemic has accelerated the development of numerous digital technologies in medicine from telemedicine to remote monitoring. Concurrently, the pandemic has resulted in huge pressures on healthcare systems. Medical imaging (MI) from chest radiographs to computed tomography and ultrasound of the thorax have played an important ro...
Preprint
Full-text available
We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye tracking system while a radiologist reviewed and reported on 1,083 CXR images. The dataset contains the following aligned data: CXR image, transcribed radiology report text, radiologist's dictation audio a...
Preprint
Pulmonary Embolism (PE) is a life-threatening disorder associated with high mortality and morbidity. Prompt diagnosis and immediate initiation of therapeutic action is important. We explored a deep learning model to detect PE on volumetric contrast-enhanced chest CT scans using a 2-stage training strategy. First, a residual convolutional neural net...
Preprint
Pulmonary embolisms (PE) are known to be one of the leading causes for cardiac-related mortality. Due to inherent variabilities in how PE manifests and the cumbersome nature of manual diagnosis, there is growing interest in leveraging AI tools for detecting PE. In this paper, we build a two-stage detection pipeline that is accurate, computationally...
Conference Paper
We propose and validate an end-to-end deep learning pipeline employing multi-label learning as a tool for creating differential diagnoses of lung pathology as well as quantifying the extent and distribution of emphysema in chest CT images. The proposed pipeline first employs deep learning based volumetric lung segmentation using a 3D CNN to extract...
Preprint
Acceleration of machine learning research in healthcare is challenged by lack of large annotated and balanced datasets. Furthermore, dealing with measurement inaccuracies and exploiting unsupervised data are considered to be central to improving existing solutions. In particular, a primary objective in predictive modeling is to generalize well to b...
Conference Paper
Full-text available
We explore a solution for learning disease signatures from weakly, yet easily obtainable, annotated volumetric medical imaging data by analyzing 3D volumes as a sequence of 2D images. We demonstrate the performance of our solution in the detection of emphysema in lung cancer screening low-dose CT images. Our approach utilizes convolutional long sho...
Article
Full-text available
EMR systems are intended to improve patient-centered care management and hospital administrative processing. However, the information stored in EMRs can be disorganized, incomplete, or inconsistent, creating problems at the patient and system level. We present a technology that reconciles inconsistencies between clinical diagnoses and administrativ...
Preprint
Full-text available
We explore a solution for learning disease signatures from weakly, yet easily obtainable, annotated volumetric medical imaging data by analyzing 3D volumes as a sequence of 2D images. We demonstrate the performance of our solution in the detection of emphysema in lung cancer screening low-dose CT images. Our approach utilizes convolutional long sho...
Conference Paper
In this paper we present a new method of uncovering patients with aortic valve diseases in large electronic health record systems through learning with multimodal data. The method automatically extracts clinically-relevant valvular disease features from five multimodal sources of information including structured diagnosis, echocardiogram reports, a...
Article
In this paper, we propose metric Hashing Forests (mHF) which is a supervised variant of random forests tailored for the task of nearest neighbor retrieval through hashing. This is achieved by training independent hashing trees that parse and encode the feature space such that local class neighborhoods are preserved and encoded with similar compact...
Conference Paper
Radiologists and cardiologists today have to view large amounts of imaging data relatively quickly leading to eye fatigue. Further, they have only limited access to clinical information relying mostly on their visual interpretation of imaging studies for their diagnostic decisions. In this paper, we present Medical Sieve, an automated cognitive ass...
Patent
Embodiments of the invention relate to automating image classification with respect to coronary vessels in an angiography sequence. Two primary elements are employed, including training and recognition. Training pertains to the pre-processing images and extracting salient features that characterize the appearance of coronary arteries under differen...
Patent
Full-text available
A method for recognizing heart diseases in a cardiac echo video of a heart with an unknown disease using a spatio-temporal disease model derived from a training echo video, comprising the steps of: generating a plurality of training models for heart diseases, wherein the cardiac echo videos are each derived from a known viewpoint and the disease of...
Patent
According to one embodiment of the present invention, a method for echocardiogram view classification is provided. According to one embodiment of the present invention, a method comprises: obtaining a plurality of video images of a subject; aligning the plurality images; using the aligned images to generate a motion magnitude image; filtering the m...
Patent
Systems and methods providing automated extraction of information contained in video data and uses thereof are described. In particular, systems and associated methods are described that provide techniques for extracting data embedded in video, for example measurement-value pairs of medical videos, for use in a variety of applications, for example...
Patent
Continuous wave Doppler images in a data base comprising cardiac echo studies are processed to separate Doppler frames. The frames are pre-processed to extract envelope curves and their corner shape features. Shape patterns in Doppler images from echo studies of patients with known cardiac (valvular) diseases are employed to infer the similarity in...
Conference Paper
Automatic detection of coronary stenosis in X-ray angiography data is a challenging problem. The low contrast between vessels and surrounding tissue, as well as large intensity gradients within the image, make detection of vessels and stenoses difficult. In this paper we exploit the spatiotemporal nature of the angiography sequences to present a ro...
Conference Paper
Full-text available
In this paper, we address discrimination between normal and abnormal left ventricular shapes by capturing deviations from the normal appearance through a new parametric distorted elliptic shape model. To apply the parametric description, we automatically locate the left ventricular region in 4-chamber views and extract its bounding contours and pos...
Patent
Full-text available
A method for recognizing heart diseases in a cardiac echo video of a heart with an unknown disease using a spatio-temporal disease model derived from a training echo video, comprising the steps of: generating a plurality of training models for heart diseases, wherein the cardiac echo videos are each derived from a known viewpoint and the disease of...
Article
To provide quick diagnostic insights to medical practitioners into echocardiograms by only analyzing the echocardiogram workflows (defined as the sequence of modalities examined). We define a dictionary of workflows, called subflows, which are commonly encountered in echocardiography workflows but are mutually exclusive. We represent each workflow...
Conference Paper
In this paper we address the problem of finding similar coronary angiograms from a database of angiograms using a new constrained nonrigid shape model for the description of coronary arteries. The model captures the non-rigid variations in the artery shapes while still preserving the overall perceptual spatial layout based on the articulation const...
Conference Paper
Data is only as good as the similarity metric used to compare it. The all important notion of similarity allows us to leverage knowledge derived from prior observations to predict characteristics of new samples. In this paper we consider the problem of compiling a consistent and accurate view of similarity given its multiple incomplete and noisy ap...
Conference Paper
This paper presents a predictive space aggregated regression based boosting algorithm, and its application in classifying the Continuous Wave(CW) Flow Doppler image data set with the diseases of stenosis and regurgitation in mitral and aortic valves. The proposed algorithm involves finding a way to simultaneously combine all the weak learners based...
Article
This paper describes two real-time computer vision systems created 10 years ago that detect and track people in stores to obtain insights of customer behavior while shopping. The first system uses a single color camera to identify shopping groups in the checkout line. Shopping groups are identified by analyzing the inter-body distances coupled with...
Conference Paper
In clinical practice, physicians often exploit previously observed patterns in coronary angiograms from similar patients to quickly assess the state of the disease in a current patient. These assessments involve visually observed features such as the distance of a junction from the root and the tortuosity of the arteries. In this paper, we show how...
Conference Paper
Due to poor image quality as well as the difficulty of modeling the non-rigid heart motion, motion information has rarely been used in the past for angiogram analysis. In this paper we propose a new motion feature for the purpose of classifying angiogram videos according to their viewpoints. Specifically, local motion content of the video around th...
Conference Paper
Coronary angiography is routinely used to screen patients both prior to and during angioplasty. Each angiography study results in a collection of video sequences or runs that depict coronary arteries from different viewpoints. A key problem to be addressed in the automatic interpretation of coronary angiography videos is the identification of image...
Conference Paper
Full-text available
Recent advances in healthcare and bioscience technologies and proliferation of portable medical devices have produce massive amount of multimodal data, the need for parallel processing is apparent for mining these data sets, which can range anywhere from tens of gigabytes, to terabytes or even petabytes. AALIM (Advanced Analytics for Information Ma...
Conference Paper
Full-text available
In this paper we address the problem of automatic selection of important vessel-depicting key frames within 2D angiography videos. Two different methods of frame selection are described, one based on Frangi filter, and the other based on detecting parallel curves formed from edges in angiography images. Results are shown by comparison to physician...
Conference Paper
Full-text available
Echocardiography provides important morphological and functional details of the heart which can be used for the diagnosis of various cardiac diseases. Most of the existing automatic cardiac disease recognition systems that use echocardiograms are either based on unreliable anatomical region detection (e.g. left ventricle) or require extensive manua...
Conference Paper
Full-text available
Flow Doppler imaging has become an integral part of an echocardiographic exam. Automated interpretation of flow doppler imaging has so far been restricted to obtain- ing hemodynamic information from velocity-time profiles depicted in these images. In this paper we exploit the shape patterns in Doppler images to infer the similarity in valvu- lar di...
Conference Paper
Full-text available
With the growing image collection on the web, classifying images has become an actively explored problem. In this paper we present a novel approach to the classification of images depicting objects in a category using the odd-man-out principle of visual categorization. Specifically, we build a model of an object category by noting discriminative fe...
Article
Modern Electronic Medical Record (EMR) systems often integrate large amounts of data from multiple disparate sources. To do so, EMR systems must align the data to create consistency between these sources. The data should also be presented in a manner that allows a clinician to quickly understand the complete condition and history of a patient's hea...
Conference Paper
Full-text available
In this paper, we propose a generalized group-wise non-rigid registration strategy for multiple unlabeled point-sets of unequal cardinality, with no bias toward any of the given point-sets. To quantify the divergence between the probability distributions--specifically Mixture of Gaussians--estimated from the given point sets, we use a recently deve...
Conference Paper
Echocardiography is often used to diagnose cardiac diseases related to regional and valvular motion abnormalities. Due to the low resolution of the imaging modality, the choice of viewpoint and mode, and the experience of the sonographers, there is a large variance in the estimation of important diagnostic measurements such as ejection fraction. In...
Article
In an 2D echocardiogram exam, an ultrasound probe samples the heart with 2D slices. Changing the orientation and position on the probe changes the slice viewpoint, altering the cardiac anatomy being imaged. The determination of the probe viewpoint forms an essential step in automatic cardiac echo image analysis. In this paper we present a system fo...
Conference Paper
Full-text available
Echo videos are an important modality for cardiac decision support. In addition to describing the shape and motion of the heart, they capture important diagnostic measurements as textual feature-value pairs that are good indicators of the underlying disease. In this paper, we describe reliable extraction of such textual information through selectiv...
Conference Paper
Full-text available
With the rise of tools for clinical decision support, there is an increased need for automatic processing of electrocardiograms (ECG) documents. In fact, many systems have already been developed to perform signal processing tasks such as 12-lead off-line ECG analysis and real-time patient monitoring. All these applications require an accurate detec...
Conference Paper
Full-text available
During a 2D echo exam, the transducer position is varied to elicit important information about the heart function and its anatomy. Knowledge of the transducer viewpoint is important in automatic cardiac echo interpretation to understand the regions being depicted as well as in the quantification of their attributes. In this paper, we address the pr...
Conference Paper
Full-text available
In this paper we present a method of simultaneous registration of an entire sequence of frames of an echocardiographic sequence. In our approach, each echo frame is modeled using a probability density function, and registration problem between all pairs of echo frames is formulated as the problem of matching probability densities. An information-th...
Conference Paper
Full-text available
2D Echocardiography is an important diagnostic aid for morphological and functional assessment of the heart. The transducer position is varied during an echo exam to elicit important information about the heart function and its anatomy. The knowledge of the transducer viewpoint is important in automatic cardiac echo interpretation to understand the...
Article
In this paper we present a method of automatic disease recognition by using statistical spatio-temporal disease models in cardiac echo videos. Starting from echo videos of known viewpoints as training data, we form a statistical model of shape and motion information within a cardiac cycle for each disease. Specifically, an active shape model (ASM)...
Conference Paper
Full-text available
In order to maximize online reading performance and comprehension, how should a designer choose typographical variables such as font size and font type? This paper presents an eye tracking study of how font size and font type affect online reading. In a between-subjects design, we collected data from 82 subjects reading stories formatted in a varie...
Conference Paper
Full-text available
Diagnostic decision support is still very much an art for physicians in their practices today due to lack of quantitative tools. AALIM is a decision support system for cardiology that exploits the consensus opinions of other physicians who have looked at similar patients, to present statistical reports summarizing possible diagnoses. The key idea b...
Conference Paper
Full-text available
Heart auscultation and ECG are two very important and commonly used diagnostic aids in cardiovascular disease diagnosis. Physicians routinely perform diagnosis from simple heart auscultation and visual examination of ECG waveform shapes. It is common knowledge to physicians that patients with the same disease have similar-looking ECG shapes and com...
Conference Paper
Full-text available
Disease-specific understanding of echocardiographic sequences requires accurate characterization of spatio-temporal motion patterns. In this paper we present a method of automatic extraction and matching of spatio-temporal patterns from cardiac echo videos. Specifically, we extract cardiac regions (chambers and walls) using a variation of multiscal...
Conference Paper
Full-text available
We present an eye tracking study to measure if and how including pictures – relevant or irrelevant to the text – affects online reading. In a between-subjects design, 82 subjects read a story on a computer screen. The text was accompanied by either: (a) pictures related to the text, (b) pictures unrelated to the text (advertisements), or (c) no pic...
Article
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995. Includes bibliographical references (p. 173-184). by David James Beymer. Ph.D.
Article
Books, newspapers, and magazines have lines of text no more than five or six inches wide. The rationale behind the line lengths is simple: The shorter the line, the easier it is to read. A recent IBM study has expanded upon that finding, revealing that shorter line lengths also makes information easier to retain. IBM Learning partnered with scienti...
Article
Full-text available
Disease-specific understanding of echocardiographic sequences requires accurate characterization of spatio-temporal motion patterns. In this paper we present a method of automatic extraction and matching of spatio-temporal patterns from cardiac echo videos. Specifically, we extract cardiac regions (chambers and walls) using a variation of multiscal...
Article
An electrocardiogram (ECG) is an important and commonly used diagnostic aid in cardiovascular disease diagnosis. Physicians routinely perform diagnosis by a simple visual examination of ECG waveform shapes. In this paper, we address the problem of shape-based retrieval of ECG recordings, both digital and scanned from paper, to infer similarity in d...
Conference Paper
Full-text available
We developed and studied an experimental system, RealTourist, which lets a user to plan a conference trip with the help of a remote tourist consultant who could view the tourist's eye-gaze superimposed onto a shared map. Data collected from the experiment were analyzed in conjunction with literature review on speech and eye-gaze patterns. This insp...
Conference Paper
Full-text available
How wide should paragraphs be formatted for optimal reader reten- tion and ease of reading? While everyone is familiar with the narrow, multi- column formatting in newspapers and magazines, research on the issue is not consistent. Early work using printed media favored narrow formatting, while more recent work using computer monitors has favored wi...
Conference Paper
Full-text available
Capturing and analyzing the detailed eye movements of a user while reading a web page can reveal much about the ways in which web reading occurs. The WebGazeAnalyzer system described here is a remote-camera system, requiring no invasive head-mounted apparatus, giving test subjects a normal web use experience when performing web-based tasks. While m...
Article
The correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. This representation has two components: (1) shape, or (x,...
Article
Junctions are the intersection points of three or more intensity surfaces in an image. An analysis of zero crossings and the gradient near junctions demonstrates that gradient-based edge detection schemes fragment edges at junctions. This fragmentation is caused by the intrinsic pairing of zero crossings and a destructive interference of edge gradi...
Article
Recent investigations have shown the advantages of keeping multiple hypotheses during visual tracking. In this paper we explore an alternative method that keeps just a single hypothesis per tracked object for computational e#ciency, but displays robust performance and recovery from error by employing continuous detection during tracking. The method...
Conference Paper
In the eye gaze tracking problem, the goal is to determine where on a monitor screen a computer user is looking, ie., the gaze point. Existing systems generally have one of two limitations: either the head must remain fixed in front of a stationary camera, or, to allow for head motion, the user must wear an obstructive device. We introduce a 3D eye...
Conference Paper
The paper describes how to detect human posture and upper body parts using overhead narrow-baseline stereo cameras. This information is extracted to understand retail customer behavior while shopping. We propose an approach to detect body posture without using an explicit 3D human model. The proposed method is based on a 3D silhouette, a silhouette...