Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

The Noloco Strategy For Essential Hypertension, F. Matthew Mihelic Md

Faculty Publications

Ninety-nine percent of all “essential” hypertension can be controlled by using the NoLoCo strategy, without causing any significant side-effects and without an increase in insulin resistance. NoLoCo stands for Norvasc (amlodipine), Lozol (indapamide), and Cozaar (losartan), but the medicines are considered and used in reverse order.

Utilizing The System Engineering Trade Study Analysis Method To Analyze Patient Aeromedical Evacuation, Sara Shaghaghi, Jeremy M. Slagley, Michael E. Miller, Gaiven Varshney

Faculty Publications

The US Air Force has gone through many aeromedical patient isolation transport system designs. The first designs were developed in response to the Ebola outbreak in 2014 and, more recently, the COVID-19 pandemic. The trade study analysis part of the system engineering design method was used to analyze the historic and current aeromedical patient contamination control transport systems. A trade study is a process that evaluates alternatives based upon various “-ilities”, such as reconfigurability, flexibility, durability, cost, and more, and performs a systematic analysis to aid designers in producing a ‘good’ design alternative given the large set of possible solutions. …

Perspectives Of African American Women About Barriers To Breast Cancer Prevention And Screening Practices: A Qualitative Study, Abosede F. Obikunle, Jochebed Bosede Ade-Oshifogun

Faculty Publications

Breast cancer is a severe illness that often has fatal consequences. Adherence to the recommendations for breast cancer surveillance is poorly practiced among African American women. The study aimed to identify barriers to preventative screening for breast cancer among African American women (AAW) using a qualitative research design. We explored the influence of personal barriers, stereotypes, socioeconomic status, culture, attitudes, and beliefs on African American women's behavior regarding breast cancer screening. Fourteen African American women were interviewed. Data analysis was completed with Interpretative Phenomenology Approach (IPA). This study's findings demonstrated that African American women perceived the barriers to breast cancer …

Updates In The Pharmacologic Prophylaxis And Treatment Of Invasive Candidiasis In The Pediatric And Neonatal Intensive Care Units, James Hunter Fly, Seerat Kapoor, Kelly Bobo, Jeremy S. Stultz

Faculty Publications

Purpose of review The goal of this review was to provide an update on the prevention and treatment options for invasive candidiasis (IC) in the neonatal intensive care unit (NICU) and pediatric intensive care unit (PICU).

Recent findings Studies have further validated the use of fluconazole for IC prophylaxis among high-risk patients in the NICU. It remains unclear if prophylaxis leads to resistance development and the ideal dosage regimen is still not clear. Recent studies have been published comparing caspofungin and micafungin to amphotericin B and illustrated similar efficacy outcomes in the NICU. Micafungin now has approval from the United …

Ultra-Conformal Skin Electrodes With Synergistically Enhanced Conductivity For Long-Time And Low-Motion Artifact Epidermal Electrophysiology, Yan Zhao, Song Zhang, Tianhao Yu, Yan Zhang, Guo Ye, Han Cui, Chengzhi He, Wenchao Jiang, Yu Zhai, Chunming Lu, Xiaodan Gu, Nan Liu

Faculty Publications

Accurate and imperceptible monitoring of electrophysiological signals is of primary importance for wearable healthcare. Stiff and bulky pregelled electrodes are now commonly used in clinical diagnosis, causing severe discomfort to users for long-time using as well as artifact signals in motion. Here, we report a ~100 nm ultra-thin dry epidermal electrode that is able to conformably adhere to skin and accurately measure electrophysiological signals. It showed low sheet resistance (~24 Ω/sq, 4142 S/cm), high transparency, and mechano-electrical stability. The enhanced optoelectronic performance was due to the synergistic effect between graphene and poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), which induced a high …

A Novel Method For Ecg Signal Classification Via One-Dimensional Convolutional Neural Network, Xuan Hua, Jungang Han, Chen Zhao, Haipeng Tang, Zhuo He, Qinghui Chen, Shaojie Tang, Jinshan Tang, Weihua Zhou

Faculty Publications

This paper develops an end-to-end ECG signal classification algorithm based on a novel segmentation strategy and 1D Convolutional Neural Networks (CNN) to aid the classification of ECG signals and alleviate the workload of physicians. The ECG segmentation strategy named R-R-R strategy (i.e., retaining ECG data between the R peaks just before and after the current R peak) is used for segmenting the original ECG data into segments to train and test the 1D CNN models. The novel strategy mimics physicians in scanning ECG to a greater extent, and maximizes the inherent information of ECG segments for diagnosis. The performance of …

Criterion Validation And Interpretability Of The Single Assessment Numerical Evaluation (Sane) Of Self-Reported Recovery In Patients With Neck Pain, Elizabeth Oakley, Chad E. Cook, Bryan O'Halloran

Faculty Publications

Background

The SANE is a PROM of recovery, which may assist clinicians in clinical decision-making and discharge planning. The psychometric measurement properties of the SANE have yet to be determined for neck pain.

Objectives

Threefold objectives included: 1)determine the numerical threshold for the SANE at which patients with neck pain determine their symptoms are acceptable; 2)determine the association between scores for the NDI and VAS, with the SANE; 3)determine the average number of visits, costs and value associated with the management of neck pain.

Design

Longitudinal repeated measures cohort design.

Methods

Threshold measures for self-reported recovery with the …

Generalized Deep Learning Eeg Models For Cross-Participant And Cross-Task Detection Of The Vigilance Decrement In Sustained Attention Tasks, Alexander J. Kamrud [*], Brett J. Borghetti, Christine M. Schubert Kabban, Michael E. Miller

Faculty Publications

Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these tasks including air traffic control, watchkeeping, baggage inspection, and many others. Recent research into physiological markers of mental fatigue indicate that markers exist which extend across all individuals and all types of vigilance tasks. This suggests that it would be possible to build an EEG model which detects these markers and the subsequent vigilance decrement in any task (i.e., a task-generic model) and in any person (i.e., a cross-participant model). However, thus far, no task-generic EEG …

3d Fusion Between Fluoroscopy Angiograms And Spect Myocardial Perfusion Images To Guide Percutaneous Coronary Intervention, Haipeng Tang, Robert R. Bober, Chen Zhao, Chaoyang Zhang, Huiqing Zhu, Zhuo He, Zhihui Xu, Weihua Zhou

Faculty Publications

Background

Percutaneous coronary intervention (PCI) in stable coronary artery disease (CAD) is commonly triggered by abnormal myocardial perfusion imaging (MPI). However, due to the possibilities of multivessel disease, serial stenoses and variability of coronary artery perfusion distribution, an opportunity exists to better align anatomic stenosis with perfusion abnormalities to improve revascularization decisions. This study aims to develop a multi-modality fusion approach to assist decision-making for PCI.

Methods and Results

Coronary arteries from fluoroscopic angiography (FA) were reconstructed into 3D artery anatomy. Left ventricular (LV) epicardial surface was extracted from SPECT. The artery anatomy and epicardial surface were non-rigidly fused. The …

Machine Learning For The Preliminary Diagnosis Of Dementia, Fubao Zhu, Xiaonan Li, Haipeng Tang, Zhuo He, Chaoyang Zhang, Guang-Uei Hung, Pai-Yi Chiu, Weihua Zhou

Faculty Publications

Objective: The reliable diagnosis remains a challenging issue in the early stages of dementia. We aimed to develop and validate a new method based on machine learning to help the preliminary diagnosis of normal, mild cognitive impairment (MCI), very mild dementia (VMD), and dementia using an informant-based questionnaire.

Methods: We enrolled 5,272 individuals who filled out a 37-item questionnaire. In order to select the most important features, three different techniques of feature selection were tested. Then, the top features combined with six classification algorithms were used to develop the diagnostic models.

Results: Information Gain was the most …

Fully Automated Bone Age Assessment On Large-Scale Hand X-Ray Dataset, Xiaoyang Pan, Yizhe Zhao, Hao Chen, De Wei, Chen Zhao, Zhi Wei

Faculty Publications

Bone age assessment (BAA) is an essential topic in the clinical practice of evaluating the biological maturity of children. Because the manual method is time-consuming and prone to observer variability, it is attractive to develop computer-aided and automated methods for BAA. In this paper, we present a fully automatic BAA method. To eliminate noise in a raw X-ray image, we start with using U-Net to precisely segment hand mask image from a raw X-ray image. Even though U-Net can perform the segmentation with high precision, it needs a bigger annotated dataset. To alleviate the annotation burden, we propose to use …

Using The Clinical Frailty Scale To Predict The Length Of Stay In Otolaryngology Unit In Taiwan, Wei-Kang Tung, Hsiang-Chin Hung, Wei-Chen Tung

Faculty Publications

Frailty was a common syndrome in geriatric clinic and general internal medical wards. Some authors had identified the Clinical Frailty Scale (CFS) as a predictor of length of stay in the acute medicine unit. However, the role of the Clinical Frailty Scale in the length of stay in otolaryngology unit had not been well studied. The objective of this study was to find out the correlation of the CFS in elderly patients admitted to otolaryngology unit and their length of stay. A retrospective medical chart review of 203 elderly patients admitted to the otolaryngology ward from January, 2014 to December, …

Deep Learning-Based Structure-Activity Relationship Modeling For Multi-Category Toxicity Classification: A Case Study Of 10k Tox21 Chemicals With High-Throughput Cell-Based Androgen Receptor Bioassay Data, Gabriel Idakwo, Sundar Thangapandian, Joseph Luttrell Iv, Zhaoxian Zhou, Chaoyang Zhang, Ping Gong

Faculty Publications

Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for in silico predictive toxicology than existing shallow learning algorithms. However, contradicting reports have been documented. To further explore the advantages of DL over shallow learning, we conducted this case study using two cell-based androgen receptor (AR) activity datasets with 10K chemicals generated from the Tox21 program. A nested double-loop cross-validation approach was adopted along with a stratified sampling strategy for partitioning chemicals of multiple AR activity classes (i.e., agonist, antagonist, inactive, and inconclusive) at the same distribution rates amongst the training, validation …

Machine Learning For Prediction Of Sudden Cardiac Death In Heart Failure Patients With Low Left Ventricular Ejection Fraction: Study Protocol For A Retrospective Multicentre Registry In China, Fanqi Meng, Zhihua Zhang, Xiaofeng Hou, Zhiyong Qian, Yao Wang, Yanhong Chen, Yilian Wang, Ye Zhou, Zhen Chen, Xiwen Zhang, Jing Yang, Jinlong Zhang, Jianghong Guo, Kebei Li, Lu Chen, Ruijuan Zhuang, Hai Jiang, Weihua Zhou, Shaowen Tang, Yongyue Wei, Jiangang Zou

Faculty Publications

Introduction: Left ventricular ejection fraction (LVEF) ≤35%, as current significant implantable cardioverter-defibrillator (ICD) indication for primary prevention of sudden cardiac death (SCD) in heart failure (HF) patients, has been widely recognised to be inefficient. Improvement of patient selection for low LVEF (≤35%) is needed to optimise deployment of ICD. Most of the existing prediction models are not appropriate to identify ICD candidates at high risk of SCD in HF patients with low LVEF. Compared with traditional statistical analysis, machine learning (ML) can employ computer algorithms to identify patterns in large datasets, analyse rules automatically and build both linear and …

Nmd-12: A New Machine-Learning Derived Screening Instrument To Detect Mild Cognitive Impairment And Dementia, Pai-Yi Chiu, Haipeng Tang, Cheng-Yu Wei, Chaoyang Zhang, Guang-Uei Hung, Weihua Zhou

Faculty Publications

Introduction

Using machine learning techniques, we developed a brief questionnaire to aid neurologists and neuropsychologists in the screening of mild cognitive impairment (MCI) and dementia.

Methods

With the reduction of the survey size as a goal of this research, feature selection based on information gain was performed to rank the contribution of the 45 items corresponding to patient responses to the specified questions. The most important items were used to build the optimal screening model based on the accuracy, practicality, and interpretability. The diagnostic accuracy for discriminating normal cognition (NC), MCI, very mild dementia (VMD) and dementia was validated in …

A Learning-Based Automatic Segmentation And Quantification Method On Left Ventricle In Gated Myocardial Perfusion Spect Imaging: A Feasibility Study, Tonghe Wang, Yang Lei, Haipeng Tang, Zhou He, Richard Castillo, Cheng Wang, Dianfu Li, Kristin Higgins, Tian Liu, Walter J. Curran, Walter J. Curran, Weihua Zhou, Xiaofeng Yang

Faculty Publications

Background: The performance of left ventricular (LV) functional assessment using gated myocardial perfusion SPECT (MPS) relies on the accuracy of segmentation. Current methods require manual adjustments that are tedious and subjective. We propose a novel machine-learning-based method to automatically segment LV myocardium and measure its volume in gated MPS imaging without human intervention.

Methods: We used an end-to-end fully convolutional neural network to segment LV myocardium by delineating its endocardial and epicardial surface. A novel compound loss function, which encourages similarity and penalizes discrepancy between prediction and training dataset, is utilized in training stage to achieve excellent performance. …

Deep Learning Based Analysis Of Histopathological Images Of Breast Cancer, Juanying Xie, Ran Liu, Joseph Luttrell Iv, Chaoyang Zhang

Faculty Publications

Breast cancer is associated with the highest morbidity rates for cancer diagnoses in the world and has become a major public health issue. Early diagnosis can increase the chance of successful treatment and survival. However, it is a very challenging and time-consuming task that relies on the experience of pathologists. The automatic diagnosis of breast cancer by analyzing histopathological images plays a significant role for patients and their prognosis. However, traditional feature extraction methods can only extract some low-level features of images, and prior knowledge is necessary to select useful features, which can be greatly affected by humans. Deep learning …

Cause And Consequence Of Aβ: Lipid Interactions In Alzheimer Disease Pathogenesis, Vijay Rangachari, Dexter N. Dean, Pratip Rana, Ashwin Vaidya, Preetam Ghosh

Faculty Publications

Self-templating propagation of protein aggregate conformations is increasingly becoming a significant factor in many neurological diseases. In Alzheimer disease (AD), intrinsically disordered amyloid-β (Aβ) peptides undergo aggregation that is sensitive to environmental conditions. High-molecular weight aggregates of Aβ that form insoluble fibrils are deposited as senile plaques in AD brains. However, low-molecular weight aggregates called soluble oligomers are known to be the primary toxic agents responsible for neuronal dysfunction. The aggregation process is highly stochastic involving both homotypic (Aβ-Aβ) and heterotypic (Aβ with interacting partners) interactions. Two of the important members of interacting partners are membrane lipids and surfactants, to …

Myocardial Stunning-Induced Left Ventricular Dyssynchrony On Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging, Zhixin Jiang, Haipeng Tang, Jianzhou Shi, Yanli Zhou, Cheng Wang, Dianfu Li, Qijun Shan, Weihua Zhou

Faculty Publications

Objectives Myocardial stunning provides additional nonperfusion markers of coronary artery disease (CAD), especially for severe multivessel CAD. The purpose of this study is to assess the influence of myocardial stunning to the changes of left ventricular mechanical dyssynchrony (LVMD) parameters between stress and rest gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI).

Patients and methods A total of 113 consecutive patients (88 males and 25 females) who had undergone both stress and rest ^99mTc-sestamibi gated SPECT MPI were retrospectively enrolled. Suspected or known patients with CAD were included if they had exercise stress MPI and moderate to …

Patient Acceptance Of Remote Scribing Powered By Google Glass In Outpatient Dermatology: Cross-Sectional Study, Sandra Odenheimer, Deepika Goyal, Veena Jones, Ruth Rosenblum, Lam Ho, Albert Chan

Faculty Publications

Background: The ubiquitous use of electronic health records (EHRs) during medical office visits using a computer monitor and keyboard can be distracting and can disrupt patient-health care provider (HCP) nonverbal eye contact cues, which are integral to effective communication. Provider use of a remote medical scribe with face-mounted technology (FMT), such as Google Glass, may preserve patient-HCP communication dynamics in health care settings by allowing providers to maintain direct eye contact with their patients while still having access to the patient’s relevant EHR information. The medical scribe is able to chart patient encounters in real-time working in an offsite location, …

Development Of Estrogen Receptor Beta Binding Prediction Model Using Large Sets Of Chemicals, Sugunadevi Sakkiah, Chandrabose Selvaraj, Ping Gong, Chaoyang Zhang, Weida Tong, Huixiao Hong

Faculty Publications

We developed an ER_β binding prediction model to facilitate identification of chemicals specifically bind ER_β or ER_α together with our previously developed ER_α binding model. Decision Forest was used to train ER_β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER_β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations …

Situation Awareness, Sociotechnical Systems, And Automation In Emergency Medical Services: Theory And Measurement, David Schuster, Dan Nathan-Roberts

Faculty Publications

No abstract provided.

Photosensitizer Drug Delivery Via An Optical Fiber, Matibur Zamadar, Goutam Ghosh, Adaic Kapillai Mahendran, Mihaela Minnis, Bonnie I. Kruft, Ashwini Ghogare, David Aebisher, Alexander Greer

Faculty Publications

: An optical fiber has been developed with a maneuverable miniprobe tip that sparges O2 gas and photodetaches pheophorbide (sensitizer) molecules. Singlet oxygen is produced at the probe tip surface which reacts with an alkene spacer group releasing sensitizer upon fragmentation of a dioxetane intermediate. Optimal sensitizer photorelease occurred when the probe tip was loaded with 60 nmol sensitizer, where crowding of the pheophorbide molecules and self-quenching were kept to a minimum. The fiber optic tip delivered pheophorbide molecules and singlet oxygen to discrete locations. The 60 nmol sensitizer was delivered into petrolatum; however, sensitizer release was less efficient in …

Singlet Oxygen Delivery Through The Porous Cap Of A Hollow-Core Fiber Optic Device, Matibur Zamadar, David Aebisher, Alexander Greer

Faculty Publications

The development of the first photosensitizer/fiber optic device is reported. An oxygen-flowing, fiber-capped configuration is used for the application of heterogeneous, spatially confined singlet oxygen delivery in aqueous media. This is a unique device, unlike other heterogeneous photosensitizers, in which local concentrations of singlet oxygen can be delivered via introduction and withdrawal of the fiber tip.

J.T.: A Case Of Mitral Valve Prolapse, F. Matthew Mihelic

Faculty Publications

No abstract provided.