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Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson Oct 2023

Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson

Turkish Journal of Electrical Engineering and Computer Sciences

Millions of people throughout the world suffer from the complicated and crippling condition of chronic pain. It can be brought on by several underlying disorders or injuries and is defined by chronic pain that lasts for a period exceeding three months. To better understand the brain processes behind pain and create prediction models for pain-related outcomes, machine learning is a potent technology that may be applied in Functional magnetic resonance imaging (fMRI) chronic pain research. Data (fMRI and T1-weighted images) from 76 participants has been included (30 chronic pain and 46 healthy controls). The raw data were preprocessed using fMRIprep …

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Trcaptionnet: A Novel And Accurate Deep Turkish Image Captioning Model With Vision Transformer Based Image Encoders And Deep Linguistic Text Decoders, Serdar Yildiz, Abbas Memi̇ş, Songül Varli Oct 2023

Trcaptionnet: A Novel And Accurate Deep Turkish Image Captioning Model With Vision Transformer Based Image Encoders And Deep Linguistic Text Decoders, Serdar Yildiz, Abbas Memi̇ş, Songül Varli

Turkish Journal of Electrical Engineering and Computer Sciences

Image captioning is known as a fundamental computer vision task aiming to figure out and describe what is happening in an image or image region. Through an image captioning process, it is ensured to describe and define the actions and the relations of the objects within the images. In this manner, the contents of the images can be understood and interpreted automatically by visual computing systems. In this paper, we proposed the TRCaptionNet a novel deep learning-based Turkish image captioning (TIC) model for the automatic generation of Turkish captions. The model we propose essentially consists of a basic image encoder, …

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Feature Distillation From Vision-Language Model For Semisupervised Action Classification, Asli Çeli̇k, Ayhan Küçükmani̇sa, Oğuzhan Urhan Oct 2023

Feature Distillation From Vision-Language Model For Semisupervised Action Classification, Asli Çeli̇k, Ayhan Küçükmani̇sa, Oğuzhan Urhan

Turkish Journal of Electrical Engineering and Computer Sciences

The training of supervised machine learning approaches is critically dependent on annotating large-scale datasets. Semisupervised learning approaches aim to achieve compatible performance with supervised methods using relatively less annotation without sacrificing good generalization capacity. In line with this objective, ways of leveraging unlabeled data have been the subject of intense research. However, semisupervised video action recognition has received relatively less attention compared to image domain implementations. Existing semisupervised video action recognition methods trained from scratch rely heavily on augmentation techniques, complex architectures, and/or the use of other modalities while distillation-based methods use models that have only been trained for 2D …

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Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima Oct 2023

Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima

Turkish Journal of Electrical Engineering and Computer Sciences

The conventional approach to creating 3D surfaces from 2D medical images is the marching cube algorithm, but it often results in rough surfaces. On the other hand, B-spline curves and nonuniform rational B-splines (NURBSs) offer a smoother alternative for 3D surface reconstruction. However, NURBSs use control points (CTPs) to define the object shape and corners play an important role in defining the boundary shape as well. Thus, in order to fill the research gap in applying corner detection (CD) methods to generate the most favorable CTPs, in this paper corner points are identified to predict organ shape. However, CTPs must …

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Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur Oct 2023

Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur

Turkish Journal of Electrical Engineering and Computer Sciences

Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is the basic prerequisite for disease diagnosis and treatment planning. However, achieving precise lung segmentation poses significant challenges due to factors such as variations in anatomical shape and size, the presence of strong edges at the rib cage and clavicle, and overlapping anatomical structures resulting from diverse diseases. Although commonly considered as the de-facto standard in medical image segmentation, the convolutional UNet architecture and its variants …

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Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi Oct 2023

Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi

Turkish Journal of Electrical Engineering and Computer Sciences

Explainable AI (XAI) improved by a deep neural network (DNN) of a residual neural network (ResNet) and long short-term memory networks (LSTMs), termed XAIRL, is proposed for segmenting foot infrared imaging datasets. First, an infrared sensor imaging dataset is acquired by a foot infrared sensor imaging device and preprocessed. The infrared sensor image features are then defined and extracted with XAIRL being applied to segment the dataset. This paper compares and discusses our results with XAIRL. Evaluation indices are applied to perform various measurements for foot infrared image segmentation including accuracy, precision, recall, F1 score, intersection over union (IoU), Dice …

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Self-Dual Systems For Backscattering Cancellation, Nasim Mohammadi Estrakhri Oct 2023

Self-Dual Systems For Backscattering Cancellation, Nasim Mohammadi Estrakhri

Engineering Faculty Articles and Research

Using carefully arranged electric and magnetic components, we have recently demonstrated that backscattering from otherwise arbitrarily shaped two- and three-dimensional structures can be fully eliminated. Here, first we investigate the possibility of creating self-dual microwave absorbers that may provide advantages compared to typical commercial magnetoelectric absorbers. Next, we demonstrate that the self-duality condition is not limited to homogenous structures and may be extended to effective material properties, opening the door to realistic implementation of these structures at microwave and optical frequencies.

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Computationally Efficient Design, Diagnosis, And Test Of Analog Integrated Circuit Analysis, Nisharg Shah Oct 2023

Computationally Efficient Design, Diagnosis, And Test Of Analog Integrated Circuit Analysis, Nisharg Shah

Computer Science and Engineering Theses and Dissertations

With the modern trend in chip functionalities and chip size, considerable advancement
has been made in EDA (Electronic Design Automation). EDA algorithms have become
irreplaceable in the semiconductor industry. We use adjoint sensitivity analysis and transient
simulations to render runtimes affordable and responses accurate.
This dissertation presents various advantages of adjoint sensitivity analysis to improve
the design cycle, provide better testing, and make more efficient the diagnosis of analog
circuits. Our motivation for all our applications has been to greatly reduce the computational
resources required while still providing the required result for design diagnosis and test.

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Hardware-In-The-Loop Reaction Wheel Testbed With Camera Vision, Abigail Romero, Harvey Perkins, Stephen Kwok-Choon Oct 2023

Hardware-In-The-Loop Reaction Wheel Testbed With Camera Vision, Abigail Romero, Harvey Perkins, Stephen Kwok-Choon

College of Engineering Summer Undergraduate Research Program

Reaction wheels are widely used in aerospace systems as a method of attitude control. This research was focused on the design, development, and testing of a hardware-in-the-loop reaction wheel testbed that can be used for research and teaching applications related to satellite navigation and control. This project successfully utilized commercial off-the-shelf components to develop a reaction wheel capable of controlling the orientation of a freely rotating platform, as well as tracking objects using computer vision.

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Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook Oct 2023

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …

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Modeling And Compensating Of Noise In Time-Of-Flight Sensors, Bryan Rodriguez Oct 2023

Modeling And Compensating Of Noise In Time-Of-Flight Sensors, Bryan Rodriguez

Electrical Engineering Theses and Dissertations

Three-dimensional (3D) sensors provide the ability to perform contactless measurements of objects and distances that are within their field of view. Unlike traditional two-dimensional (2D) cameras, which only provide RGB data about objects within a scene, 3D sensors are able to directly provide depth information for objects within a scene. Of these 3D sensing technologies, Time-of-Flight (ToF) sensors are becoming more compact which allows them to be more easily integrated with other devices and to find use in more applications. ToF sensors also provide several benefits over other 3D sensing technologies that increase the types of applications where ToF sensors …

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Robustness Of Convolutional Neural Networks: Analysis And Applications, Xin Zhang Oct 2023

Robustness Of Convolutional Neural Networks: Analysis And Applications, Xin Zhang

Theses and Dissertations

Convolutional neural networks (CNNs) have gained increasing popularity and versatility in recent decades, finding applications in diverse domains including image recognition, natural language processing, recommendation systems, as well as safety-critical areas like autonomous driving, medical diagnostics, and military fields. However, the widespread use of CNNs in safety-critical applications has also given rise to concerns regarding their robustness. The low robustness of CNNs may lead to erroneous predictions and even significant losses of human life and property, especially when dealing with corner cases or boundary cases in real-world problem-solving. Most existing methods for evaluating CNNs still heavily rely on their accuracy …

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Creating An Automatic Lowering Function For Quarter-Scale Tractor Pulling Sled, Sam Wilkins Oct 2023

Creating An Automatic Lowering Function For Quarter-Scale Tractor Pulling Sled, Sam Wilkins

Honors Program: Senior Projects (Public)

As the agricultural industry works to continuously integrate innovative technology and improve production efficiency, improved on-board data acquisition and transmission will be necessary for all agricultural machines. To make this a reality, the utilization of controller area network (CAN) technology will be crucial. Therefore, it is important for all agricultural engineers to have foundational knowledge of CAN bus systems and the standards that govern their use in industry. The UNL quarter-scale tractor team regularly utilizes CAN buses on their tractors and testing equipment. One such testing machine is the team’s pulling sled, which uses CAN messages to transport important information …

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Deep-Learning-Based Classification Of Digitally Modulated Signals, John A. Snoap Oct 2023

Deep-Learning-Based Classification Of Digitally Modulated Signals, John A. Snoap

Electrical & Computer Engineering Theses & Dissertations

This dissertation presents several novel deep-learning (DL)-based approaches for classifying digitally modulated signals, one method of which involves the use of capsule networks (CAPs) together with cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in …

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Fabrication Of Smooth Sac305 Thin Films Via Magnetron Sputtering And Evaluations Of Microstructure, Creep, And Electrical Resistivity, Manish Ojha Oct 2023

Fabrication Of Smooth Sac305 Thin Films Via Magnetron Sputtering And Evaluations Of Microstructure, Creep, And Electrical Resistivity, Manish Ojha

Mechanical & Aerospace Engineering Theses & Dissertations

SAC305 (96.5%Sn-3%Ag-0.5%Cu) is the leading alternative to the traditional Sn-Pb solder eutectic alloy owing to its low melting temperature, better compatibility with other components, and excellent mechanical/structural properties. In the realm of modern electronics, where devices are increasingly miniaturized, the design and characterization of thin solder joints become paramount. The orientation and size of the grains within the solder can influence its ability to withstand mechanical stresses. However, research on SAC thin films remains sparse, and these films present unique challenges and characteristics compared to their bulk counterparts, influenced by factors like interfaces, stresses, thickness, microstructure, and the nature of …

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On The Prediction Of The Mechanical Properties Of Limestone Calcined Clay Cement: A Random Forest Approach Tailored To Cement Chemistry, Taihao Han, Bryan K. Aylas-Paredes, Jie Huang, Ashutosh Goel, Narayanan Neithalath, Aditya Kumar Oct 2023

On The Prediction Of The Mechanical Properties Of Limestone Calcined Clay Cement: A Random Forest Approach Tailored To Cement Chemistry, Taihao Han, Bryan K. Aylas-Paredes, Jie Huang, Ashutosh Goel, Narayanan Neithalath, Aditya Kumar

Materials Science and Engineering Faculty Research & Creative Works

Limestone calcined clay cement (LC3) is a sustainable alternative to ordinary Portland cement, capable of reducing the binder's carbon footprint by 40% while satisfying all key performance metrics. The inherent compositional heterogeneity in select components of LC3, combined with their convoluted chemical interactions, poses challenges to conventional analytical models when predicting mechanical properties. Although some studies have employed machine learning (ML) to predict the mechanical properties of LC3, many have overlooked the pivotal role of feature selection. Proper feature selection not only refines and simplifies the structure of ML models but also enhances these models' prediction performance and interpretability. This …

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Low-Voltage Ride-Through Capability Improvement Of Type-3 Wind Turbine Through Active Disturbance Rejection Feedback Control-Based Dynamic Voltage Restorer, El M. Boulaoutaq, Asma Aziz, Abdelmounime El Magri, Ahmed Abbou, Mohamed Ajaamoum, Azeddine Rachdy Oct 2023

Low-Voltage Ride-Through Capability Improvement Of Type-3 Wind Turbine Through Active Disturbance Rejection Feedback Control-Based Dynamic Voltage Restorer, El M. Boulaoutaq, Asma Aziz, Abdelmounime El Magri, Ahmed Abbou, Mohamed Ajaamoum, Azeddine Rachdy

Research outputs 2022 to 2026

Disconnections due to voltage drops in the grid cannot be permitted if wind turbines (WTs) contribute significantly to electricity production, as this increases the risk of production loss and destabilizes the grid. To mitigate the negative effects of these occurrences, WTs must be able to ride through the low-voltage conditions and inject reactive current to provide dynamic voltage support. This paper investigates the low-voltage ride-Through (LVRT) capability enhancement of a Type-3 WT utilizing a dynamic voltage restorer (DVR). During the grid voltage drop, the DVR quickly injects a compensating voltage to keep the stator voltage constant. This paper proposes an …

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Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris Oct 2023

Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris

Electrical & Computer Engineering Theses & Dissertations

Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA …

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Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara Oct 2023

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

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Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor Oct 2023

Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor

Faculty Publications

To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952-2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in a sensor. Recent work has sought to overcome the graphical nature and visual-inspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but …

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Designing A Model Of Solar Photovoltaic Water Pumping System For Off-Grid Localities In Tanzania, Imani Mruma Sep 2023

Designing A Model Of Solar Photovoltaic Water Pumping System For Off-Grid Localities In Tanzania, Imani Mruma

Tanzania Journal of Engineering and Technology (TJET)

Modeling of photovoltaic (PV) water pumping system for rural water localities is vital especially in these modern days, in Tanzania. This is due to the rise of high number of solar-powered rural water projects constructed lacking appropriate design. The fate result into poor and substandard projects delivering below expectations. Kikombo Solar Water Project situated in Dodoma; Tanzania is one among poorly designed solar project chosen as a case study to validate proposed model. The main problem of Kikombo project is unsatisfactory amount of water from domestic points to satisfy population demand. This matter has been raised by pumping-station attendants and …

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Designing A Cylindrical Capacitive Based Sensor For Monitoring The Table Salt’S Moisture Content During Iodization, Mwajuma Lungo Sep 2023

Designing A Cylindrical Capacitive Based Sensor For Monitoring The Table Salt’S Moisture Content During Iodization, Mwajuma Lungo

Tanzania Journal of Engineering and Technology (TJET)

Coaxial cylinder capacitive moisture sensor for determination of moisture content of table salts has been fabricated. The CMS method for determination of moisture content of table salts overcomes the effect of evaporation of iodine in table salt which results from heating in the oven drying method. The CMS overcomes the polarization effect result from the resistive methods of moisture content determination and it is non expensive to construct and it has high accuracy since measurements involves programming system in interpretation of the results. In this research, moisture content sensor based on capacitive principal created using two coaxial cylinders with height …

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Comparison Of End-Point Energies Of Bremsstrahlung Photons From 28 Ghz Ecr Ion Source In Three Measurement Locations, Mwingereza John Kumwenda Dr Sep 2023

Comparison Of End-Point Energies Of Bremsstrahlung Photons From 28 Ghz Ecr Ion Source In Three Measurement Locations, Mwingereza John Kumwenda Dr

Tanzania Journal of Engineering and Technology (TJET)

Bremsstrahlung photons measurement show elevated energy emission beyond critical energy in 28-GHz ECR and its nature is not revealed. Thus, the aim of this study is to unveil the nature of high end-point energies at the three measurement locations. Bremsstrahlung photons from a 28-GHz ECR ion source were measured at Busan center of Korean Basic Science Institute (KBSI). The gamma-ray detection system consists of three round type NaI(Tl) scintillation detectors placed 62 cm radially from the beam axis at the three measurement locations namely injection, centre and extraction sides of an ECR ion source, and a NaI(Tl) scintillation detector placed …

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Joint Intent Detection And Slot Filling For Turkish Natural Language Understanding, Osman Büyük Sep 2023

Joint Intent Detection And Slot Filling For Turkish Natural Language Understanding, Osman Büyük

Turkish Journal of Electrical Engineering and Computer Sciences

Intent detection and slot filling are two crucial subtasks of a text-based goal-oriented dialogue system. In a goal-oriented dialogue system, users interact with the system to complete a goal (or to fulfill their intent) and provide the necessary information (slot values) to achieve that goal. Therefore, a user?s text input includes information about the user?s intent and contains required slot values. Recently, joint models that simultaneously detect the intent and extract the slots are proposed to benefit from the interaction between the two tasks. The proposed methods are usually tested using benchmark data sets in English such as ATIS and …

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Recognizing Handwritten Digits Using Spiking Neural Networks With Learning Algorithms Based On Sliding Mode Control Theory, Yeşi̇m Öni̇z, Mehmet Ayyildiz Sep 2023

Recognizing Handwritten Digits Using Spiking Neural Networks With Learning Algorithms Based On Sliding Mode Control Theory, Yeşi̇m Öni̇z, Mehmet Ayyildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a spiking neural network (SNN) has been proposed for recognizing the digits written on the LCD screen of an experimental setup. The convergence of the learning algorithm has been ensured by using sliding mode control (SMC) theory and the Lyapunov stability method for the adaptation of the network parameters. The spike response model (SRM) has been utilized in the design of the SNN. The performance of the proposed learning scheme has been evaluated both on the experimental data and on the MNIST dataset. The simulated and experimental results of the SNN structure have been compared with the …

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A Machine Learning Approach For Dyslexia Detection Using Turkish Audio Records, Tuğberk Taş, Muhammed Abdullah Bülbül, Abas Haşi̇moğlu, Yavuz Meral, Yasi̇n Çalişkan, Gunay Budagova, Mücahi̇d Kutlu Sep 2023

A Machine Learning Approach For Dyslexia Detection Using Turkish Audio Records, Tuğberk Taş, Muhammed Abdullah Bülbül, Abas Haşi̇moğlu, Yavuz Meral, Yasi̇n Çalişkan, Gunay Budagova, Mücahi̇d Kutlu

Turkish Journal of Electrical Engineering and Computer Sciences

Dyslexia is a learning disorder, characterized by impairment in the ability to read, spell, and decode letters. It is vital to detect dyslexia in earlier stages to reduce its effects. However, diagnosing dyslexia is a time-consuming and costly process. In this paper, we propose a machine-learning model that predicts whether a Turkish-speaking child has dyslexia using his/her audio records. Therefore, our model can be easily used by smart phones and work as a warning system such that children who are likely to be dyslexic according to our model can seek an examination by experts. In order to train and evaluate, …

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Stepwise Dynamic Nearest Neighbor (Sdnn): A New Algorithm For Classification, Deni̇z Karabaş, Derya Bi̇rant, Peli̇n Yildirim Taşer Sep 2023

Stepwise Dynamic Nearest Neighbor (Sdnn): A New Algorithm For Classification, Deni̇z Karabaş, Derya Bi̇rant, Peli̇n Yildirim Taşer

Turkish Journal of Electrical Engineering and Computer Sciences

Although the standard k-nearest neighbor (KNN) algorithm has been used widely for classification in many different fields, it suffers from various limitations that abate its classification ability, such as being influenced by the distribution of instances, ignoring distances between the test instance and its neighbors during classification, and building a single/weak learner. This paper proposes a novel algorithm, called stepwise dynamic nearest neighbor (SDNN), which can effectively handle these problems. Instead of using a fixed parameter k like KNN, it uses a dynamic neighborhood strategy according to the data distribution and implements a new voting mechanism, called stepwise voting. Experimental …

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Design And Characterization Of 2.4ghz Antennas For Wireless Sensor Applications, Luis Zogby Brennan Sep 2023

Design And Characterization Of 2.4ghz Antennas For Wireless Sensor Applications, Luis Zogby Brennan

Dissertations and Theses

Wireless sensor networks benefit greatly from advances in circuit integration and miniaturization. However, antennas are bound to specific geometries both in terms of fundamental limits and their response to immediate surroundings. As such, various successful techniques for antenna miniaturization must still be carefully tested and characterized as part of the design process of a sensor system. The work presented here fully characterizes a number of miniaturized 2.4GHz antennas and successfully integrates designs into a sensor system using the highly integrated Single Chip Micro Mote (SCµM), which uses a crystal-less radio design resulting in the requirement of only a …

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Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated With Postoperative Delirium, Simon T. Dillon, Sarinnapha M. Vasunilashorn, Hasan H. Otu, Long Ngo, Tamara Fong, Xuesong Gu, Michele Cavallari, Alexandra Touroutoglou, Mouhsin Shafi, Sharon K. Inouye, Zhongcong Xie, Edward R. Marcantonio, Towia A. Libermann Sep 2023

Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated With Postoperative Delirium, Simon T. Dillon, Sarinnapha M. Vasunilashorn, Hasan H. Otu, Long Ngo, Tamara Fong, Xuesong Gu, Michele Cavallari, Alexandra Touroutoglou, Mouhsin Shafi, Sharon K. Inouye, Zhongcong Xie, Edward R. Marcantonio, Towia A. Libermann

Department of Electrical and Computer Engineering: Faculty Publications

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected …

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Better Models For High-Stakes Tasks, Jacob Ryan Epifano Sep 2023

Better Models For High-Stakes Tasks, Jacob Ryan Epifano

Theses and Dissertations

The intersection of machine learning and healthcare has the potential to transform medical diagnosis, treatment, and research. Machine learning models can analyze vast amounts of medical data and identify patterns that may be too complex for human analysis. However, one of the major challenges in this field is building trust between users and the model. Due to things like high false alarm rate and the black box nature of machine learning models, patients and medical professionals need to understand how the model arrives at its recommendations. In this work, we present several methods that aim to improve machine learning models …

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