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The impact of patient clinical information on automated skin cancer detection

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arXiv 2019年

作者： Pacheco, Andre G.C. Krohling, Renato R. Graduate Program in Computer Science PPGI Federal University of Espírito Santo UFES Av. Fernando Ferrari 514 Vitória-ES Brazil Production Engineering Department Graduate Program in Computer Science PPGI Federal University of Espírito Santo UFES Av. Fernando Ferrari 514 Vitória-ES Brazil

Skin cancer is one of the most common types of cancer around the world. For this reason, over the past years, different approaches have been proposed to assist detect it. Nonetheless, most of them are based only on dermoscopy images and do not take into account the patient clinical information. In this work, first, we present a new dataset that contains clinical images, acquired from smartphones, and patient clinical information of the skin lesions. Next, we introduce a straightforward approach to combine the clinical data and the images using different well-known deep learning models. These models are applied to the presented dataset using only the images and combining them with the patient clinical information. We present a comprehensive study to show the impact of the clinical data on the final predictions. The results obtained by combining both sets of information show a general improvement of around 7% in the balanced accuracy for all models. In addition, the statistical test indicates significant differences between the models with and without considering both data. The improvement achieved shows the potential of using patient clinical information in skin cancer detection and indicates that this piece of information is important to leverage skin cancer detection systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Dermatology

Anomaly Detection in Climate Data Using Stacked and Densely Connected Long Short-Term Memory Model

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Journal of computers (Taiwan) 2020年第4期31卷 42-53页

作者： Saleh Abbas, Bahtiar Wahyono, Teguh Heryadi, Yaya Soeparno, Haryono Doctor of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Industrial Engineering Bina Nusantara University Jakarta Indonesia

Climate anomalies are considered as an important factor closely related to many disasters causing many human losses, such as airline crash, wildfires, drought and flooding in many areas. Many researchers have projected that the rising global temperature will increase the draught, especially in the mid-latitude areas. Taking those problems into account, studies on anomaly detection in climate are crucial. While climate prediction aims to analyze and model regular pattern of climate, climate anomaly studies aim to model climate deviation from its previous general patterns. Long Short Term Memory (LSTM) is a method employed in this research because it has been proven to work effectively in several anomaly detection studies, especially for data with similar characteristics. This paper presents empirical results of using Basic LSTM, Densely Connected (DC) LSTM, and Stacked-DC LSTM models to detect temperature anomaly as a manifestation of climate change in Semarang City. The results show that Stacked DC LSTM produced higher accuracy in detecting anomaly than the other two methods. © 2020 computer Society of the Republic of China. All rights reserved.

关键词： Long short-term memory

RECENT ADVANCES IN DEEP LEARNING APPLIED TO SKIN CANCER DETECTION

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arXiv 2019年

Skin cancer is a major public health problem around the world. Its early detection is very important to increase patient prognostics. However, the lack of qualified professionals and medical instruments are significant issues in this field. In this context, over the past few years, deep learning models applied to automated skin cancer detection have become a trend. In this paper, we present an overview of the recent advances reported in this field as well as a discussion about the challenges and opportunities for improvement in the current models. In addition, we also present some important aspects regarding the use of these models in smartphones and indicate future directions we believe the field will take. Copyright © 2019, The Authors. All rights reserved.

关键词： Dermatology

Spinal functional Magnetic Resonance Imaging (fMRI) on Human Studies: A Literature Review

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Spinal functional Magnetic Resonance Imaging (fMRI) on Human...

Advances in science and engineering Technology International Conferences

作者： Sajedah Al-Momani Salam Dhou Biomedical Engineering Graduate Program American University of Sharjah Sharjah UAE Department of Computer Science and Engineering American University of Sharjah Sharjah UAE

Spinal functional Magnetic Resonance Imaging (fMRI) is a newly emerging non-invasive imaging technique that has been introduced to study the Blood Oxygenation Level Dependent (BOLD) changes in the spinal cord associated with a certain activity or even at rest. Spinal fMRI is also used to assess the treatment of many dysfunctions affect the spinal cord such as spinal cord injury (SCI) and Multiple sclerosis (MS). The purpose of this paper is to propose a literature review of spinal fMRI studies performed on healthy human volunteers. The studies reviewed are divided based on the paradigm being performed during image acquisition into (1) studies under activities and stimulus which are further classified according to the type of the stimuli, and (2) studies at resting state. Moreover, the limitations of spinal fMRI and how to tackle them are discussed.

关键词： Spinal fMRI BOLD contrast Spinal fMRI limitations

Review of Image-Guided Percutaneous Coronary Interventions

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Review of Image-Guided Percutaneous Coronary Interventions

Advances in science and engineering Technology International Conferences

作者： Aseel Alatoom Jumana Farhat Salam Dhou Biomedical Engineering Graduate Program American University of Sharjah Sharjah UAE Department of Computer Science and Engineering American University of Sharjah Sharjah UAE

Image-guided surgery (IGS) involves using surgical instruments tracking system to guide the surgeon during invasive surgical procedures. The use of preoperative or intraoperative images is very essential in providing navigation for different medical applications. In this paper, a literature review of different imaging modalities that aid in the diagnosis and treatment of coronary artery disease (CAD) is proposed. The imaging modalities discussed include x-ray fluoroscopy, coronary computed tomography angiography (CCTA), fractional flow reserve (FFR), cardiac single-photon emission computed tomography (SPECT), cardiovascular magnetic resonance imaging (CMRI) and ultrasound. Additionally, pseudoaneurysms, which can result from percutaneous coronary interventions (PCI) procedure, are reviewed as well as the treatment procedure. Finally, a comparison between the different imaging modalities is carried out, based on the number of papers that have been published, in addition to the sensitivity and specificity for each modality according to PubMed and Web of science databases.

关键词： Coronary artery disease Image-guided interventions Percutaneous coronary intervention X-ray Computed tomography Fractional flow reserve Ultrasound Single photon emission computed tomography Magnetic resonance imaging Pseudoaneurysm

Biphenylene monolayer as a two-dimensional nonbenzenoid carbon allotrope: A first-principles study

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arXiv 2021年

作者： Bafekry, Asadolah Faraji, M. Fadlallah, M.M. Jappor, H.R. Karbasizadeh, S. Ghergherehchi, M. Gogova, D. Department of Radiation Application Shahid Beheshti University Tehran*** Iran Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Faculty of Science Benha University Benha13518 Egypt Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Physics University of Oslo P.O. Box 1048 Blindern Oslo Norway

In a very recent accomplishment, the two-dimensional form of Biphenylene network (BPN) has been successfully fabricated [Fan et al., science, 372, 852-856 (2021)]. Motivated by this exciting experimental result on 2D layered BPN structure, herein we perform detailed density functional theory-based first-principles calculations, for the first time, in order to gain insight into the structural, electronic and optical properties of this promising nanomaterial. Our theoretical results reveal the BPN structure is constructed from three rings of tetragon, hexagon and octagon, meanwhile the electron localization function shows very strong bonds between the C atoms in the structure. The dynamical stability of BPN is verified via the phonon band dispersion calculations. The mechanical properties reveal the brittle behavior of BPN monolayer. The Young's modulus has been computed as 0.1 TPa, which is smaller than the corresponding value of graphene, while the Poisson's ratio determined to be 0.26 is larger than that of graphene. The band structure is evaluated to show the electronic features of the material;determining the BPN monolayer as metallic with a band gap of zero. The optical properties (real and imaginary parts of the dielectric function, and the absorption spectrum) uncover BPN as an insulator along the zz direction, while owning metallic properties in xx and yy directions. We anticipate that our discoveries will pave the way to the successful implementation of this new 2D allotrope of carbon in advanced nanoelectronics. © 2021, CC BY.

关键词： Monolayers

Corrigendum to "Novel model of multiple sclerosis induced by EBV-like virus generate a unique B cell population" [Journal of Neuroimmunology volume 394 (2024) 578408]

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Journal of neuroimmunology 2025年 404卷 578625页

作者： J L Deffenbaugh K-J Jung S P Murphy Y Liu C N Rau C Petersen-Cherubini P L Collins D Chung A E Lovett-Racke Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA. Department of Computer Science and Engineering The Ohio State University USA. Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA Neuroscience Graduate Program The Ohio State University USA. Department of Biomedical Informatics The Ohio State University Wexner Medical Center USA Pelotonia Institute for Immuno-Oncology The Ohio State University Wexner Medical Center USA. Department of Neuroscience The Ohio State University Wexner Medical Center USA. Electronic address: amylovettracke@***.

Impact of Intention to Use to a Document Management System (Case Study Approach) 3

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Impact of Intention to Use to a Document Management System (...

3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Hartono, Sugiarto Kosala, Raymondus Raymond Supangkat, Suhono Harso Ranti, Benny Information Systems Department Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781538658215

Document management system makes user to access information anytime and anywhere. The purpose of this research is to analyze what variables have impact on the intention to use of document management system. To achieve the objectives conducted by identification problem on the research model developed from the model of Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology to the use of document management system. Furthermore, the data obtained from the respondents tested outer model, inner model test, hypothesis test and to produce a comprehensive analysis will be conducted Importance Performance Analysis. This research will result in a comprehensive analysis and able to provide recommendations and solutions for improvement from the implementation DMS has been done earlier. © 2018 IEEE.

关键词： Information services

iPhantom: a framework for automated creation of individualized computational phantoms and its application to CT organ dosimetry

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arXiv 2020年

作者： Fu, Wanyi Sharma, Shobhit Abadi, Ehsan Iliopoulos, Alexandros-Stavros Wang, Qi Lo, Joseph Y. Sun, Xiaobai Segars, William P. Samei, Ehsan Department of Electrical and Computer Engineering Carl E. Ravin Advanced Imaging Laboratories Duke University DurhamNC27705 United States Department of Physics Carl E. Ravin Advanced Imaging Laboratories Duke University DurhamNC27705 United States Department of Computer Science Duke University DurhamNC27708 United States Department of Radiology Fourth Clinical Hospital of Hebei Medical University Heibei050011 China Departments of Electrical and Computer Engineering Biomedical Engineering Medical Physics Graduate Program Carl E. Ravin Advanced Imaging Laboratories Duke University DurhamNC27705 United States Departments of Biomedical Engineering Medical Physics Graduate Program and Radiology Carl E. Ravin Advanced Imaging Laboratories Duke University DurhamNC27705 United States Carl E. Ravin Advanced Imaging Laboratories Medical Physics Graduate Program Departments of Radiology Electrical and Computer Engineering Biomedical Engineering and Physics Duke University DurhamNC27705 United States

Objective: This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or "digital-twins (DT)" using patient medical images. The framework is applied to assess radiation dose to radiosensitive organs in CT imaging of individual patients. Method: From patient CT images, iPhantom segments selected anchor organs (e.g. liver, bones, pancreas) using a learning-based model developed for multi-organ CT segmentation. Organs challenging to segment (e.g. intestines) are incorporated from a matched phantom template, using a diffeomorphic registration model developed for multi-organ phantom-voxels. The resulting full-patient phantoms are used to assess organ doses during routine CT exams. Result: iPhantom was validated on both the XCAT (n=50) and an independent clinical (n=10) dataset with similar accuracy. iPhantom precisely predicted all organ locations with good accuracy of Dice Similarity Coefficients (DSC) >0.6 for anchor organs and DSC of 0.3-0.9 for all other organs. iPhantom showed Copyright © 2020, The Authors. All rights reserved.

关键词： Phantoms