Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …

List Of 121 Papers Citing One Or More Skin Lesion Image Datasets, Neda Alipour

Other resources

No abstract provided.

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D

Articles

Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …

Metasurface Cloaks To Decouple Closely Spaced Printed Dipole Antenna Arrays Fed By A Microstrip-To-Balanced Transmission-Line Transition, Doojin Lee, Alexander B. Yakovlev

Faculty and Student Publications

In this work, we present a numerical study of 1D and 2D closely spaced antenna arrays of microstrip dipole antennas covered by a metasurface in order to properly cloak and decouple the antenna arrays operating at neighboring frequencies. We show that the two strongly coupled arrays fed by a microstrip-to-balanced transmission-line transition are effectively decoupled in 1D and 2D array scenarios by covering the dipole antenna elements with an elliptically shaped metasurface. The metasurface comprises sub-wavelength periodic metallic strips printed on an elliptically shaped dielectric cover around the dipole antennas and integrated with the substrate. We present a practical design …

Breast Cancer Detection From Histopathology Images Using Machine Learning Techniques: A Bibliometric Analysis, Shubhangi A. Joshi, Anupkumar M. Bongale Dr., Arunkumar M. Bongale Dr.

Library Philosophy and Practice (e-journal)

Computer aided diagnosis has become upcoming area of research over past few years. With the advent of machine learning and especially deep learning techniques, the scenario of work flow management in healthcare sector is changing drastically. Artificial intelligence has shown potential in the field of breast cancer care. With datasets for machine learning frameworks getting eventually richer with time, we can definitely get newer insights in the field of breast cancer care. This will help in narrowing down the treatment range for patients and increasing patient survivability. The purpose of this study was to perform bibliometric analysis of the literature …

A Brief Bibliometric Survey Of Explainable Ai In Medical Field, Nilkanth Mukund Deshpande, Shilpa Shailesh Gite

Library Philosophy and Practice (e-journal)

_{^{Background: This study aims to analyze the work done in the field of explainability related to artificial intelligence, especially in the medical field from 2004 onwards using the bibliometric methods.}}

_{^{Methods: different articles based on the topic leukemia detection were retrieved using one of the most popular database- Scopus. The articles are considered from 2004 onwards. Scopus analyzer is used for different types of analysis including documents by year, source, county and so on. There are other different analysis tools such as VOSviewer Version 1.6.15. This is used for the analysis of different units such as co-authorship, co-occurrences, citation analysis …}}

Improve The Prototype Of Low-Cost Near-Infrared Diffuse Optical Imaging System, Chen Xu, Mohammed Z. Shakil

Publications and Research

Diffuse Optical Tomography (DOT) and Optical Spectroscopy using near-infrared (NIR) diffused light has demonstrated great potential for the initial diagnosis of tumors and in the assessment of tumor vasculature response to neoadjuvant chemotherapy. The aims of this project are 1) to test the different types of LEDs in the near-infrared range, and design the driving circuit, and test the modulation of LEDs at different frequencies; 2) to test the APDs as a detector, and build the receiver system and compare efficiency with pre-built systems. In this project, we are focusing on creating a low-cost infrared transmission system for tumor and …

Wetting-Driven Formation Of Present-Day Loess Structure, Yanrong Li, Weiwei Zhang, Shengdi He, Adnan Aydin

Faculty and Student Publications

© 2020 The Authors Present-day loess, especially Malan loess formed in Later Quaternary, has a characteristic structure composed of vertically aligned strong units and weak segments. Hypotheses describing how this structure forms inside original loess deposits commonly relate it to wetting-drying process. We tested this causal relationship by conducting unique experiments on synthetic samples of initial loess deposits fabricated by free-fall of loess particles. These samples were subjected to a wetting-drying cycle, and their structural evolutions were documented by close-up photography and CT scanning. Analysis of these records revealed three key stages of structural evolution: initiation (evenly distributed cracks appear …

A Mathematical Framework For Estimating Risk Of Airborne Transmission Of Covid-19 With Application To Face Mask Use And Social Distancing, Rajat Mittal, Charles Meneveau, Wen Wu

Faculty and Student Publications

© 2020 Author(s). A mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19 is presented. The model employs basic concepts from fluid dynamics and incorporates the known scope of factors involved in the airborne transmission of such diseases. Simplicity in the mathematical form of the model is by design so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries but it can also be understandable by a broad audience outside science and academia. The caveats and limitations of the model are discussed in detail. The model …

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is …

Machine Learning Approaches For Fracture Risk Assessment: A Comparative Analysis Of Genomic And Phenotypic Data In 5130 Older Men, Qing Wu, Fatma Nasoz, Jongyun Jung, Bibek Bhattarai, Mira V. Han

Public Health Faculty Publications

The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Study (n = 5130), were analyzed. After a comprehensive genotype imputation, genetic risk score (GRS) was calculated from 1103 associated Single Nucleotide Polymorphisms for each participant. Data were normalized and split into a training set (80%) and a validation set (20%) for analysis. Random forest, gradient boosting, neural network, and logistic regression were used to develop prediction models for major osteoporotic fractures …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

Scalable Profiling And Visualization For Characterizing Microbiomes, Camilo Valdes

FIU Electronic Theses and Dissertations

Metagenomics is the study of the combined genetic material found in microbiome samples, and it serves as an instrument for studying microbial communities, their biodiversities, and the relationships to their host environments. Creating, interpreting, and understanding microbial community profiles produced from microbiome samples is a challenging task as it requires large computational resources along with innovative techniques to process and analyze datasets that can contain terabytes of information.

The community profiles are critical because they provide information about what microorganisms are present in the sample, and in what proportions. This is particularly important as many human diseases and environmental disasters …

Load-Balancing Rendezvous Approach For Mobility-Enabled Adaptive Energy-Efficient Data Collection In Wsns, Jian Zhang, Jian Tang, Zhonghui Wang, Feng Wang, Gang Yu

Faculty and Student Publications

Copyright © 2020 KSII The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the …

Revisiting Lightweight Encryption For Iot Applications: Error Performance And Throughput In Wireless Fading Channels With And Without Coding, Yazid M. Khattabi, Mustafa M. Matalgah, Mohammed M. Olama

Faculty and Student Publications

© 2013 IEEE. Employing heavy conventional encryption algorithms in communications suffers from added overhead and processing time delay; and in wireless communications, in particular, suffers from severe performance deterioration (avalanche effect) due to fading. Consequently, a tremendous reduction in data throughput and increase in complexity and time delay may occur especially when information traverse resource-limited devices as in Internet-of-Things (IoT) applications. To overcome these drawbacks, efficient lightweight encryption algorithms have been recently proposed in literature. One of those, that is of particular interest, requires using conventional encryption only for the first block of data in a given frame being transmitted. …

Cooperative Relay Selection For Load Balancing With Mobility In Hierarchical Wsns: A Multi-Armed Bandit Approach, Jian Zhang, Jian Tang, Feng Wang

Faculty and Student Publications

© 2013 IEEE. Energy efficiency is the major concern in hierarchical wireless sensor networks(WSNs), where the major energy consumption originates from radios for communication. Due to notable energy expenditure of long-range transmission for cluster members and data aggregation for Cluster Head (CH), saving and balancing energy consumption is a tricky challenge in WSNs. In this paper, we design a CH selection mechanism with a mobile sink (MS) while proposing relay selection algorithms with multi-user multi-armed bandit (UM-MAB) to solve the problem of energy efficiency. According to the definition of node density and residual energy, we propose a conception referred to …

Timcc: On Data Freshness In Privacy-Preserving Incentive Mechanism Design For Continuous Crowdsensing Using Reverse Auction, Xiaoqiang Ma, Weiwei Deng, Feng Wang, Menglan Hu, Fei Chen, Mohammad Mehedi Hassan

Faculty and Student Publications

© 2013 IEEE. As an emerging paradigm that leverages the wisdom and efforts of the crowd, mobile crowdsensing has shown its great potential to collect distributed data. The crowd may incur such costs and risks as energy consumption, memory consumption, and privacy leakage when performing various tasks, so they may not be willing to participate in crowdsensing tasks unless they are well-paid. Hence, a proper privacy-preserving incentive mechanism is of great significance to motivate users to join, which has attracted a lot of research efforts. Most of the existing works regard tasks as one-shot tasks, which may not work very …

How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Can the rubber-hand illusion be extended to a moving robotic arm in different degrees of freedom (DOF), inducing sense of ownership & agency over the arm? We hypothesize that DOF closer to what humans possess will result in a stronger sense of ownership and agency.

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

Urea Functionalization Of Ultrasound-Treated Biochar: A Feasible Strategy For Enhancing Heavy Metal Adsorption Capacity, Baharak Sajjadi, James William Broome, Wei Yin Chen, Daniell L. Mattern, Nosa O. Egiebor, Nathan Hammer, Cameron L. Smith

Faculty and Student Publications

© 2018 Elsevier B.V. The main objective of a series of our researches is to develop a novel acoustic-based method for activation of biochar. This study investigates the capability of biochar in adsorbing Ni(II) as a hazardous contaminant and aims at enhancing its adsorption capacity by the addition of extra nitrogen and most probably phosphorous and oxygen containing sites using an ultrasono-chemical modification mechanism. To reach this objective, biochar physically modified by low-frequency ultrasound waves (USB) was chemically treated by phosphoric acid (H3PO4) and then functionalized by urea (CO(NH2)2). Cavitation induced by ultrasound waves exfoliates and breaks apart the regular …

Mechanically Assisted Electrochemical Degradation Of Alumina-Tic Composites, Hetal Umesh Maharaja, Guigen Zhang

Publications

Alumina-TiC composite material is a tough ceramic composite with excellent hardness, wear resistance and oxidation resistance in dry and high-temperature conditions. In aqueous conditions, however, it is likely to be electrochemically active facilitating charge transfer processes due to the conductive nature of TiC. For application as an orthopedic biomaterial, it is crucial to assess the electrochemical behavior of this composite, especially under a combined mechanical and electrochemical environment. In this study, we examined the mechanically assisted electrochemical performance of alumina-TiC composite in an aqueous environment. The spontaneous electrochemical response to brushing abrasion was measured. Changes in the magnitude of electrochemical …

Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we develop a framework for E-health Cyber Ecosystems, and look into different involved actors. The three interested parties in the ecosystem including patients, doctors, and healthcare providers are discussed in 3 different phases. In Phase 1, machine-learning based modeling and simulation analysis is performed to remotely predict a patient's risk level of having heart diseases in real time. In Phase 2, an online dynamic queueing model is devised to pair doctors with patients having high risk levels (diagnosed in Phase 1) to confirm the risk, and provide help. In Phase 3, a decision making paradigm is proposed …

Design Of A Flexible Control Platform And Miniature In Vivo Robots For Laparo-Endoscopic Single-Site Surgeries, Lou P. Cubrich

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Minimally-invasive laparoscopic procedures have proven efficacy for a wide range of surgical procedures as well as benefits such as reducing scarring, infection, recovery time, and post-operative pain. While the procedures have many advantages, there are significant shortcomings such as limited instrument motion and reduced dexterity. In recent years, robotic surgical technology has overcome some of these limitations and has become an effective tool for many types of surgeries. These robotic platforms typically have an increased workspace, greater dexterity, improved ergonomics, and finer control than traditional laparoscopic methods. This thesis presents the designs of both a four degree-of-freedom (DOF) and 5-DOF …

Characterization Of Molecular Communication Based On Cell Metabolism Through Mutual Information And Flux Balance Analysis, Zahmeeth Sayed Sakkaff

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Synthetic biology is providing novel tools to engineer cells and access the basis of their molecular information processing, including their communication channels based on chemical reactions and molecule exchange. Molecular communication is a discipline in communication engineering that studies these types of communications and ways to exploit them for novel purposes, such as the development of ubiquitous and heterogeneous communication networks to interconnect biological cells with nano and biotechnology-enabled devices, i.e., the Internet of Bio-Nano Things. One major problem in realizing these goals stands in the development of reliable techniques to control the engineered cells and their behavior from the …

Design And Development Of Two Component Hydrogel Ejector For Three-Dimensional Cell Growth, Thomas Dunkle, Jessica Deschamps, Connie Dam

Honors Scholar Theses

Hydrogels are useful in wound healing, drug delivery, and tissue engineering applications, but the available methods of injecting them quickly and noninvasively are limited. The medical industry does not yet have access to an all-purpose device that can quickly synthesize hydrogels of different shapes and sizes. Many synthesis procedures that have been developed result in the formation of amorphous hydrogels. While generally useful, amorphous hydrogels exhibit limited capability in tissue engineering applications, especially due to their viscous properties. This endeavor aims to modulate the appropriate gelation parameters, optimize the injection process, and create a prototype that allows for the extrusion …

Vcare: A Personal Emergency Response System To Promote Safe And Independent Living Among Elders Staying By Themselves In Community Or Residential Settings, Priyankar Bhattacharjee

Computer and Electronics Engineering: Dissertations, Theses, and Student Research

‘Population aging’ is a growing concern for most of us living in the twenty first century, primarily because many of us in the next few years will have a senior person to care for - spending money towards their healthcare expenditures AND/OR having to balance a full-time job with the responsibility of care-giving, travelling from another city to be with this elderly citizen who might be our parent, grand-parent or even community elders. As informal care-givers, if somehow we were able to monitor the day-to-day activities of our elderly dependents, and be alerted when wrong happens to them that would …

Collaborative Research: North East Cyberinfrastructure Consortium, Michael Eckardt, Vicki Nemeth, Carolyn Mattingly

University of Maine Office of Research Administration: Grant Reports

The North East Cyberinfrastructure Consortium has finished its third year of Track-2 funding. In this report we summarize our overall progress and progress for Year 3.

In 2006, we began to organize as the five North Eastern EPSCoR states (ME, NH, VT, Rl, DE) around cyberinfrastructure. The box below describes the state of cyberinfrastructure in 2008 by which time we had developed the North East Cyberinfrastructure Consortium to position ourselves for grant opportunities that would help us to address our cyber deficits.

The Track-2 collaborative proposal submitted in January 2009 was designed to address these barriers in order enable our …

Activity Intent Recognition Of The Torso Based On Surface Electromyography And Inertial Measurement Units, Zhe Zhang

Masters Theses 1911 - February 2014

This thesis presents an activity mode intent recognition approach for safe, robust and reliable control of powered backbone exoskeleton. The thesis presents the background and a concept for a powered backbone exoskeleton that would work in parallel with a user. The necessary prerequisites for the thesis are presented, including the collection and processing of surface electromyography signals and inertial sensor data to recognize the user’s activity. The development of activity mode intent recognizer was described based on decision tree classification in order to leverage its computational efficiency. The intent recognizer is a high-level supervisory controller that belongs to a three-level …

Evaluating And Training Intraoperative Analysis Of The Mitral Valve, Neil A. Tenenholtz

Link Foundation Modeling, Simulation and Training Fellowship Reports

Mitral valve repair is the recommended method of treating valve incompetency. However, the procedure is quite difficult and, as a result, underperformed due to surgeon’s need to predict the closed valve shape of the patient’s arrested heart. While the interactive process of predicting closed valve shape is achieved by physically manipulating valve tissue (known as valve analysis), surgical training consists of traditional, non-interactive pedagogy (e.g., book-based learning and lectures) followed by an apprenticeship model where the trainee is gradually given hands-on experience, resulting in post-medical school training that is often 10 years or greater. The continuing education of practicing cardiac …