Diagnosis Commons^™

Correlation Enhanced Distribution Adaptation For Prediction Of Fall Risk, Ziqi Guo, Teresa Wu, Thurmon Lockhart, Rahul Soangra, Hyunsoo Yoon

Physical Therapy Faculty Articles and Research

With technological advancements in diagnostic imaging, smart sensing, and wearables, a multitude of heterogeneous sources or modalities are available to proactively monitor the health of the elderly. Due to the increasing risks of falls among older adults, an early diagnosis tool is crucial to prevent future falls. However, during the early stage of diagnosis, there is often limited or no labeled data (expert-confirmed diagnostic information) available in the target domain (new cohort) to determine the proper treatment for older adults. Instead, there are multiple related but non-identical domain data with labels from the existing cohort or different institutions. Integrating different …

Classification Of Colorectal Cancer Using Resnet And Efficientnet Models, Abhishek Ranjan, Priyanshu Srivastva, B Prabadevi, R Sivakumar, Rahul Soangra, Shamala K. Subramaniam

Physical Therapy Faculty Articles and Research

Introduction:

Cancer is one of the most prevalent diseases from children to elderly adults. This will be deadly if not detected at an earlier stage of the cancerous cell formation, thereby increasing the mortality rate. One such cancer is colorectal cancer, caused due to abnormal growth in the rectum or colon. Early screening of colorectal cancer helps to identify these abnormal growth and can exterminate them before they turn into cancerous cells.

Aim:

Therefore, this study aims to develop a robust and efficient classification system for colorectal cancer through Convolutional Neural Networks (CNNs) on histological images.

Methods:

Despite challenges in …

Digital 3d Brain Mri Arterial Territories Atlas, Chin-Fu Liu, Johnny Hsu, Xin Xu, Ganghyun Kim, Shannon M. Sheppard, Erin L. Meier, Michael I. Miller, Argye E. Hillis, Andreia V. Faria

Communication Sciences and Disorders Faculty Articles and Research

The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

Optimal Multi-Stage Arrhythmia Classification Approach, Jianwei Zhang, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, Guohua Fu, Hai Yao, Dongbo Li, Hangyuan Guo, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead …

A 12-Lead Electrocardiogram Database For Arrhythmia Research Covering More Than 10,000 Patients, Jianwei Zhang, Jianming Zhang, Sidy Daniako, Hai Yao, Hangyuan Guo, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

This newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People’s Hospital (Shaoxing Hospital Zhejiang University School of Medicine) and aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. Certain types of arrhythmias, such as atrial fibrillation, have a pronounced negative impact on public health, quality of life, and medical expenditures. As a non-invasive test, long term ECG monitoring is a major and vital diagnostic tool for detecting these conditions. This practice, however, generates large amounts of data, the analysis of which requires considerable …

The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch

Mathematics, Physics, and Computer Science Faculty Articles and Research

Osteoporosis is the most common metabolic bone disease and goes largely undiagnosed throughout the world, due to the inaccessibility of DXA machines. Multivariate analyses of serum bone turnover markers were evaluated in 226 Orange County, California, residents with the intent to determine if serum osteocalcin and serum pyridinoline cross-links could be used to detect the onset of osteoporosis as effectively as a DXA scan. Descriptive analyses of the demographic and lab characteristics of the participants were performed through frequency, means and standard deviation estimations. We implemented logistic regression modeling to find the best classification algorithm for osteoporosis. All calculations and …

Alzheimer’S Disease: Dawn Of A New Era?, Farideh Amirrad, Emira Bousoik, Kiumars Shamloo, Hassan Al-Shiyab, Viet-Hong Nguyen, Hamidreza Montazeri Aliabadi

Pharmacy Faculty Articles and Research

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by a progressive decline in cognition and memory, leading to significant impairment in daily activities and ultimately death. It is the most common cause of dementia, the prevalence of which increases with age; however, age is not the only predisposing factor. The pathology of this cognitive impairing disease is still not completely understood, which has limited the development of valid therapeutic options. Recent years have witnessed a wide range of novel approaches to combat this disease, so that they greatly increased our understanding of the disease and of the unique drug …

Abuela, Anne Walsh

Physician Assistant Studies Faculty Articles and Research

"How could I, the student admitting this patient on behalf of the attending physician, ever identify and address her medical issues if we couldn't effectively communicate? How could I help her understand the medications, consultations, tests, and procedures she'd receive, not to mention the grueling regimen of daily physical therapy, occupational therapy, speech and swallowing therapy, counseling psychology, and social work sessions?"

Associations Between Modifiable Health-Risk Behaviors And Personality Types, Jon C. Schommer, Paul D. Tieger, Anthony W. Olson, Lawrence M. Brown

Pharmacy Faculty Articles and Research

Objectives: The first objective for this study was to explore if characteristics of personality type (using the Preferred Communication Style Questionnaire) are associated with the following modifiable health-risk behaviors: smoking, exercise, alcohol consumption, nutrition, sleep, depression-related stress, anxiety-related stress, healthcare professional usage, and self-discipline. The second objective for this study was to explore if characteristics of personality type are associated with (1) the quality of patient-physician relationships, (2) patient-physician communication, and (3) preferred method for receiving information.

Methods: Data were collected from 10,500 adult individuals residing in the United States via an on-line, self-administered survey coordinated by Qualtrics …