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Article
Open AccessMultimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection
Recent advancements in deep learning have led to a resurgence of medical imaging and Electronic Medical Record (EMR) models for a variety of applications, including clinical decision support, automated workflo...
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Article
A Scalable Natural Language Processing for Inferring BT-RADS Categorization from Unstructured Brain Magnetic Resonance Reports
The aim of this study is to develop an automated classification method for Brain Tumor Reporting and Data System (BT-RADS) categories from unstructured and structured brain magnetic resonance imaging (MR) repo...
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Article
Open AccessFusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
Advancements in deep learning techniques carry the potential to make significant contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis, prognosis, and treatment decisio...
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Article
Open AccessPrediction of age-related macular degeneration disease using a sequential deep learning approach on longitudinal SD-OCT imaging biomarkers
We propose a hybrid sequential prediction model called “Deep Sequence”, integrating radiomics-engineered imaging features, demographic, and visual factors, with a recursive neural network (RNN) model in the sa...
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Article
Open AccessAuthor Correction: PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Article
Open AccessPENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
Pulmonary embolism (PE) is a life-threatening clinical problem and computed tomography pulmonary angiography (CTPA) is the gold standard for diagnosis. Prompt diagnosis and immediate treatment are critical to ...
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Chapter and Conference Paper
Automatic Breast Cancer Cohort Detection from Social Media for Studying Factors Affecting Patient-Centered Outcomes
Breast cancer patients often discontinue their long-term treatments, such as hormone therapy, increasing the risk of cancer recurrence. These discontinuations may be caused by adverse patient-centered outcomes...
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Article
Open AccessAutomated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm
Radiological measurements are reported in free text reports, and it is challenging to extract such measures for treatment planning such as lesion summarization and cancer response assessment. The purpose of th...
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Article
Open AccessProbabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives
We propose a deep learning model - Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) for estimating short-term life expectancy (>3 months) of the patients by analyzing fre...
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Article
Open AccessSupporting shared hypothesis testing in the biomedical domain
Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pat...
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Article
Open AccessComputerized Prediction of Radiological Observations Based on Quantitative Feature Analysis: Initial Experience in Liver Lesions
We propose a computerized framework that, given a region of interest (ROI) circumscribing a lesion, not only predicts radiological observations related to the lesion characteristics with 83.2% average predicti...
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Article
Semantics-driven annotation of patient-specific 3D data: a step to assist diagnosis and treatment of rheumatoid arthritis
In the digital era, patient-specific 3D models (3D-PSMs) are becoming increasingly relevant in computer-assisted diagnosis, surgery training on digital models, or implant design. While advanced imaging and rec...
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Article
Semantic annotation of 3D anatomical models to support diagnosis and follow-up analysis of musculoskeletal pathologies
While 3D patient-specific digital models are currently available, thanks to advanced medical acquisition devices, there is still a long way to go before these models can be used in clinical practice. The goal ...
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Chapter and Conference Paper
Generation of 3D Canonical Anatomical Models: An Experience on Carpal Bones
The paper discusses the initial results obtained for the generation of canonical 3D models of anatomical parts, built on real patient data. 3D canonical models of anatomy are key elements in a computer-assiste...
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Chapter
Accessing and Representing Knowledge in the Medical Field: Visual and Lexical Modalities
In the era of digitalization a large amount of medical data is produced, and many activities spanning from diagnosis to simulation and from assisted surgery to patient-specific treatment and follow-up are carr...
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Chapter and Conference Paper
An Ontology Based Framework for Domain Analysis of Interactive System
Understanding user requirement is an integral part of information system design and is critical to the success of interactive systems. It is now widely understood that successful systems and products begin wit...
