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Articles 181 - 210 of 298
Full-Text Articles in Health Information Technology
Design And Assessment Of Myoelectric Games For Prosthesis Training Of Upper Limb Amputees, Meeralakshmi Radhakrishnan, Asim Smailagic, Brian French, Daniel P. Siewiorek, Rajesh Krishna Balan
Design And Assessment Of Myoelectric Games For Prosthesis Training Of Upper Limb Amputees, Meeralakshmi Radhakrishnan, Asim Smailagic, Brian French, Daniel P. Siewiorek, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we present the design and evaluation of our system, which provides an engaging game-based pre-prosthesis training environment for upper limb transradial amputees. We believe that patients who train using such a training tool will demonstrate significantly higher improvement in functional performance tests using a myoelectric prosthesis than when conventional pre-prosthesis training protocols are used. We re-designed two simple games to be playable using three muscle contractions which are appropriate to pre-prosthesis exercises and are detected by an EMG-based arm sleeve. Through user studies conducted with 16 non-amputee subjects, we show that the proposed games are enjoyable, fun …
Reimagining Medical Education In The Age Of Ai, Steven A. Wartman, C. Donald Combs
Reimagining Medical Education In The Age Of Ai, Steven A. Wartman, C. Donald Combs
Computational Modeling & Simulation Engineering Faculty Publications
Available medical knowledge exceeds the organizing capacity of the human mind, yet medical education remains based on information acquisition and application. Complicating this information overload crisis among learners is the fact that physicians' skill sets now must include collaborating with and managing artificial intelligence (AI) applications that aggregate big data, generate diagnostic and treatment recommendations, and assign confidence ratings to those recommendations. Thus, an overhaul of medical school curricula is due and should focus on knowledge management (rather than information acquisition), effective use of AI, improved communication, and empathy cultivation.
Usability Challenges With Insulin Pump Devices In Diabetes Care: What Trainers Observe With First-Time Pump Users, Helen Birkmann Hernandez
Usability Challenges With Insulin Pump Devices In Diabetes Care: What Trainers Observe With First-Time Pump Users, Helen Birkmann Hernandez
CCAC Theses and Dissertations
Insulin pumps are designed for the self-management of diabetes mellitus in patients and are known for their complexity of use. Pump manufacturers engage trainers to teach patients how to use the devices correctly to control the symptoms of their disease. Usability research related to insulin pumps and other infusion pumps with first-time users as participants has centered on the relationship between user interface design and the effectiveness of task completion. According to prior research, the characteristics of system behavior in a real life environment remain elusive. A suitable approach to acquire information about potential usability problems encountered by first-time users …
Phr: Patient Health Record, Quinn Nelson
Phr: Patient Health Record, Quinn Nelson
Theses/Capstones/Creative Projects
The rapid development of information technology systems has expanded into multiple disciplines and results in systems that are limited by initial design and implementation: the Healthcare Information Technology (HIT) space is no different. The introduction of the Electronic Health Record (EHR) system has changed the way healthcare operates. Initial designs of these systems were focused on serving the needs of insurance companies and healthcare billing departments. Research shows that the design of EHR systems negatively impact provider-patient interactions and the care they receive. This capstone project capitalizes on the collaboration efforts between UNO and UNMC – by joining a research …
Better Inpatient Health Quality At Lower Cost: Should I Participate In The Online Healthcare Community First?, Kai Luo, Qiu-Hong Wang, Hock Hai Teo, Xi Chen
Better Inpatient Health Quality At Lower Cost: Should I Participate In The Online Healthcare Community First?, Kai Luo, Qiu-Hong Wang, Hock Hai Teo, Xi Chen
Research Collection School Of Computing and Information Systems
As policy makers across the globe look to health information technology (HIT) as a meansof improving the efficiency of the healthcare systems, it has sparked significant interestin understanding how HIT might help achieve that. While researchers have examined anddocumented the efficiency-improving effect of various institution HITs (e.g., electronicclinic pathways and telemedicine), the impacts of consumer HITs such as onlinehealthcare communities have been generally overlooked. Utilizing two unique datasetsfrom both an online healthcare community and a general hospital, we study the impactof online healthcare community on offline inpatient care efficiency. Through rigorousanalysis, we find that communications between physicians and patients on …
Living With Artificial Intelligence – Developing A Theory On Trust In Health Chatbots, Weiyu Wang, Keng Siau
Living With Artificial Intelligence – Developing A Theory On Trust In Health Chatbots, Weiyu Wang, Keng Siau
Research Collection School Of Computing and Information Systems
The current world is AI-filled and AI-fueled. Humans need to be able to live in harmony with AI. In this research, we aim to develop a theory on Trust between human and health chatbots. With the development of intelligent personal assistants, chatbots are becoming common and ubiquitous. Chatbots can behave as a conversational partner, complete information acquisition, and provide responses to inquiries. Chatbots have been widely used in the healthcare area, supporting physicians and assisting patients. The potential threats to privacy issues and the unpredictable performances of the chatbots hindered people’s trust and adoption of the new technology. This research-in-progress …
Identifying Elderly With Poor Sleep Quality Using Unobtrusive In-Home Sensors For Early Intervention, Xiaoping Ma, W K P Neranjana Nadee Rodrigo Goonawardene, Hwee-Pink Tan
Identifying Elderly With Poor Sleep Quality Using Unobtrusive In-Home Sensors For Early Intervention, Xiaoping Ma, W K P Neranjana Nadee Rodrigo Goonawardene, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Along with the upward trend in population ageing is the increasing proportion of the elderly population living alone in the community. This group is especially vulnerable as the onset of various physical, social and mental health issues may be more likely and may go undetected. However, smart homes enabled with elderly monitoring and care systems (EMCS) can now be used to alert caregivers of anomalies in the daily living patterns of the elderly. In this study, we focus on the sleep quality as the key living pattern, as it has been shown that poor sleep quality can lead to health …
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
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 …
Trusting Artificial Intelligence In Healthcare, W. Wang, Keng Siau
Trusting Artificial Intelligence In Healthcare, W. Wang, Keng Siau
Research Collection School Of Computing and Information Systems
Artificial Intelligence (AI) is able to perform at humans and even surpass human’s performances in some tasks. Recent cases about self-driving cars, cashier-free supermarket Amazon Go, and virtual assistants such as Apple’s Siri and Google Assistant have illustrated the current and future potential of AI. AI and its applications have infiltrated human’s work and daily life. It is inevitable that humans need to build a working relationship with AI and its applications. On one hand, humans can benefit from this new technology, for instance, a home robot can release housewife from mundane and monotonous tasks (Siau 2017, Siau 2018). On …
Is Information Systems Misuse Always Bad? A New Perspective On Is Misuse In Hospitals Under The Context Of Disasters, Dheyaaldin Alsalman
Is Information Systems Misuse Always Bad? A New Perspective On Is Misuse In Hospitals Under The Context Of Disasters, Dheyaaldin Alsalman
Masters Theses & Doctoral Dissertations
Although the extant literature has investigated how individuals engage in inappropriate behaviors based on the rational choice theory (RCT) (e.g., computer misconduct), the neutralization theory (e.g., IS security policies violation), and workarounds under normal situations, it has given little consideration to how individuals are involved in misuse of information systems with a good intention under the context of disasters. To fill this research gap, we propose a selfless misuse model, which offers a theoretical explanation for the concept of individuals’ selfless misuse intention under uncertainty caused by disasters. In this study, we show why employees make decisions to misuse the …
Detecting Personal Intake Of Medicine From Twitter, Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah, Jing Jiang
Detecting Personal Intake Of Medicine From Twitter, Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah, Jing Jiang
Research Collection School Of Computing and Information Systems
Mining social media messages such as tweets, blogs, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions to drug usage, and analyzing expression of sentiments related to drugs. Most of these studies are based on aggregated results from a large population rather than specific sets of individuals. In order to conduct studies at an individual level or specific groups of people, identifying posts mentioning intake of medicine by the user is necessary. Toward this objective we develop a classifier …
Security And Privacy In Smart Health: Efficient Policy-Hiding Attribute-Based Access Control, Yinghui Zhang, Dong Zheng, Robert H. Deng
Security And Privacy In Smart Health: Efficient Policy-Hiding Attribute-Based Access Control, Yinghui Zhang, Dong Zheng, Robert H. Deng
Research Collection School Of Computing and Information Systems
With the rapid development of the Internet of Things (IoT) and cloud computing technologies, smart health (s-health) is expected to significantly improve the quality of health care. However, data security and user privacy concerns in s-health have not been adequately addressed. As a well-received solution to realize fine-grained access control, ciphertext-policy attribute-based encryption (CP-ABE) has the potential to ensure data security in s-health. Nevertheless, direct adoption of the traditional CP-ABE in s-health suffers two flaws. For one thing, access policies are in cleartext form and reveal sensitive health-related information in the encrypted s-health records (SHRs). For another, it usually supports …
Foundations Of Health Information Technology (Undergraduate) Course Materials, Chi Zhang
Foundations Of Health Information Technology (Undergraduate) Course Materials, Chi Zhang
Computer Science and Information Technology Ancillary Materials
This is a collection of all materials used in Health Information Technology by Dr. Chi Zhang at Kennesaw State University, including lecture slides, assignments, and assessments, including a question bank.
Topics covered include:
- Clinical Financial Records
- Evidence-Based Medicine
- e-Prescribing
- Patient Bedside Systems
- Telemedicine
- Health Information Networks
- Cryptography
- Accreditation
- HIPAA Privacy and Security
Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek
Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek
Research Collection School Of Computing and Information Systems
Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to those of average consumers who tend to be less conscious about health? In this study, we analyze the healthy eating behaviors of active food journalers using data from MyFitnessPal. Surprisingly, our findings show that food journalers do not eat as healthily as they should despite their proclivity to health eating and …
Eat & Tell: A Randomized Trial Of Random-Loss Incentive To Increase Dietary Self-Tracking Compliance, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek, Tianjiao Yun
Eat & Tell: A Randomized Trial Of Random-Loss Incentive To Increase Dietary Self-Tracking Compliance, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek, Tianjiao Yun
Research Collection School Of Computing and Information Systems
A growing body of evidence has shown that incorporating behavioral economics principles into the design of financial incentive programs helps improve their cost-effectiveness, promote individuals' short-term engagement, and increase compliance in health behavior interventions. Yet, their effects on long-term engagement have not been fully examined. In study designs where repeated administration of incentives is required to ensure the regularity of behaviors, the effectiveness of subsequent incentives may decrease as a result of the law of diminishing marginal utility. In this paper, we introduce random-loss incentive-a new financial incentive based on loss aversion and unpredictability principles-to address the problem of individuals' …
Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu
Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu
Research Collection School Of Computing and Information Systems
A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module …
The Role Of Ehealth In Disasters: A Strategy For Education, Training And Integration In Disaster Medicine, Anthony C. Norris, Jose J. Gonzalez, David T. Parry, Richard E. Scott, Julie Dugdale, Deepak Khazanchi
The Role Of Ehealth In Disasters: A Strategy For Education, Training And Integration In Disaster Medicine, Anthony C. Norris, Jose J. Gonzalez, David T. Parry, Richard E. Scott, Julie Dugdale, Deepak Khazanchi
Information Systems and Quantitative Analysis Faculty Publications
This paper describes the origins and progress of an international project to advance disaster eHealth (DEH) – the application of eHealth technologies to enhance the delivery of healthcare in disasters. The study to date has focused on two major themes; the role of DEH in facilitating inter-agency communication in disaster situations, and the fundamental need to promote awareness of DEH in the education of disaster managers and health professionals. The paper deals mainly with on-going research on the second of these themes, surveying the current provision of disaster medicine education, the design considerations for a DEH programme for health professionals, …
Securing The Internet Of Healthcare, Michael Mattioli, Scott J. Shackelford, Steve Myers, Austin Brady, Yvette Wang, Stephanie Wong
Securing The Internet Of Healthcare, Michael Mattioli, Scott J. Shackelford, Steve Myers, Austin Brady, Yvette Wang, Stephanie Wong
Articles by Maurer Faculty
Cybersecurity, including the security of information technology (IT), is a critical requirement in ensuring society trusts, and therefore can benefit from, modern technology. Problematically, though, rarely a day goes by without a news story related to how critical data has been exposed, exfiltrated, or otherwise inappropriately used or accessed as a result of supply chain vulnerabilities. From the Russian government's campaign to influence the 2016 U.S. presidential election to the September 2017 Equifax breach of more than 140-million Americans' credit reports, mitigating cyber risk has become a topic of conversation in boardrooms and the White House, on Wall Street and …
Mapping Opioid Mortality Rates Across Treatment Capacity To Identify Need And Access, Garrett K. Wong, Justin R. Chang, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow
Mapping Opioid Mortality Rates Across Treatment Capacity To Identify Need And Access, Garrett K. Wong, Justin R. Chang, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow
Graduate Research Posters
Background: The opioid and heroin overdose epidemic is a public health emergency in the state of Virginia, resulting in the death of more than 1,100 people in 2016. In order to overcome this epidemic, we need to match the places with the greatest need for services related to substance use disorders with the appropriate healthcare workforce.
Aims: As the data about the overdose outbreak and related socioeconomic factors grow in size and complexity, data scientists have attempted to utilize big data techniques to identify communities and risk factors contributing to addiction.
Methods: Using data obtained from the …
Visualizing The Opioid Overdose With A Dynamic Heat Map To Identify And Predict Vulnerable Communities, Justin R. Chang, Garrett K. Wong, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow
Visualizing The Opioid Overdose With A Dynamic Heat Map To Identify And Predict Vulnerable Communities, Justin R. Chang, Garrett K. Wong, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow
Graduate Research Posters
Background: Opioid and heroin overdose epidemic is a public health emergency in the state of Virginia. In order to prevent overdose deaths, we need the target expertise in substance use disorders to areas with high rates of overdose. In particular, an area with an acute spike in overdoses might represent an urgent need for intervention.
Aims: The CDC urges the use of near real-time surveillance to effectively identify overdose incidence, and to coordinate community responses in the states affected by the epidemic, including Virginia. However, current opioid overdose datasets for Virginia lack adequate consistency, granularity, and temporality for …
The Efficacy Of An Emr-Enabled Text Messaging System To The Expanded Health Beliefs, Diabetes Care Profile And Hba1c Of Diabetes Mellitus Patients, Ma. Regina Justina E. Estuar, John Noel Victorino, Razel Custodio
The Efficacy Of An Emr-Enabled Text Messaging System To The Expanded Health Beliefs, Diabetes Care Profile And Hba1c Of Diabetes Mellitus Patients, Ma. Regina Justina E. Estuar, John Noel Victorino, Razel Custodio
Department of Information Systems & Computer Science Faculty Publications
As diabetes mellitus (DM) becomes a global emergency, there is a need to explore novel interventions to address problems in self – management. Literature agree in the potential of mobile phones to carry-out self-care for a wide-array of disease conditions. Diabetes Self – Management Support and Education Through Text – Messaging (DSMSET) is a low-cost, two-way text messaging system designed to deliver self - help, educational messages based on the nine (9) dimensions of health management. DSMSET serves as a plugin to SHINE OS+, an open – source electronic medical record (EMR) system. The research is also based on the …
Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong
Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for hybrid privacy-preserving clinical decision support system in fog cloud computing, called HPCS. In HPCS, a fog server uses a lightweight data mining method to securely monitor patients' health condition in real-time. The newly detected abnormal symptoms can be further sent to the cloud server for high-accuracy prediction in a privacy-preserving way. Specifically, for the fog servers, we design a new secure outsourced inner-product protocol for achieving secure lightweight single-layer neural network. Also, a privacy-preserving piecewise polynomial calculation protocol allows cloud server to securely perform any activation functions in multiple-layer neural network. Moreover, …
A Framework For Development Of Android Mobile Electronic Prescription Transfer Applications In Compliance With Security Requirements Mandated By The Australian Healthcare Industry, Kyaw Kyaw Htat
Theses: Doctorates and Masters
This thesis investigates mobile electronic transfer of prescription (ETP) in compliance with the security requirements mandated by the Australian healthcare industry and proposes a framework for the development of an Android mobile electronic prescription transfer application. Furthermore, and based upon the findings and knowledge from constructing this framework, another framework is also derived for assessing Android mobile ETP applications for their security compliance.
The centralised exchange model-based ETP solution currently used in the Australian healthcare industry is an expensive solution for on-going use. With challenges such as an aging population and the rising burden of chronic disease, the cost of …
A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui
A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui
Research Collection School Of Computing and Information Systems
Electronic Health Record (EHR) is a digital health documentary. It contains not only the health-related records but also the personal sensitive information. Therefore, how to reliably share EHR through the cloud is a challenging issue. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography prototype, which can achieve fine-grained access control as well as one-to-many encryption. In CP-ABE, access policy is attached to the ciphertext, and however, the access policy is not protected, which will also cause some privacy leakage. In this paper, we propose a policy preserving EHR system on the basis of CP-ABE. Specifically, we designed an algorithm, which …
Unobtrusive Monitoring To Detect Depression For Elderly With Chronic Illnesses, Jung-Yoon Kim, Na Liu, Hwee Xian Tan, Chao-Hsien Chu
Unobtrusive Monitoring To Detect Depression For Elderly With Chronic Illnesses, Jung-Yoon Kim, Na Liu, Hwee Xian Tan, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Mental health related disorders are common diseases, especially among the elder. Among the various mental health diseases, one potential threat to ageing-in-place is the risk of depression. In this paper, we propose a simple unobtrusive sensing system using passive infra-red motion sensors to monitor the activities of daily living of elderly, who are living alone. A feature extraction module comprising of three layers-states, events, and activities, and the corresponding algorithms are proposed to extract features. Four popular classification models-neural network, C4.5 decision tree, Bayesian network, and support vector machine are then applied to detect the severity of depression. We implement …
Predicting Potential Alzheimer Medical Condition In Elderly Using Iot Sensors - Case Study, Zhi Hao Kevin Chong, Yu Xuan Tee, Ling Jing Toh, Shi Jia Phang, Jie Ying Liew, Bertran Queck, Swapna Gottipati
Predicting Potential Alzheimer Medical Condition In Elderly Using Iot Sensors - Case Study, Zhi Hao Kevin Chong, Yu Xuan Tee, Ling Jing Toh, Shi Jia Phang, Jie Ying Liew, Bertran Queck, Swapna Gottipati
Research Collection School Of Computing and Information Systems
Ageing population would cause profound problems and the impact is already being felt today in many developed countries such as Singapore. The main concern for the Government is to help the citizens with active ageing through home ownership and good healthcare. With Internet of Things (IoT) gaining traction globally, Singapore is set to take advantage of this technology and leverage it to extend its capabilities towards a graceful Ageing-In-Place for the elderly. This ties in nicely with the expertise of SHINE Seniors project by SMU-iCity Lab, which integrates IT with healthcare in ways that creates innovative IT health solutions that …
Mining Non-Lattice Subgraphs For Detecting Missing Hierarchical Relations And Concepts In Snomed Ct, Licong Cui, Wei Zhu, Shiqiang Tao, James T. Case, Olivier Bodenreider, Guo-Qiang Zhang
Mining Non-Lattice Subgraphs For Detecting Missing Hierarchical Relations And Concepts In Snomed Ct, Licong Cui, Wei Zhu, Shiqiang Tao, James T. Case, Olivier Bodenreider, Guo-Qiang Zhang
Computer Science Faculty Publications
Objective: Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT.
Material and Methods: All non-lattice subgraphs (the structural part) in SNOMED CT are exhaustively extracted using a scalable MapReduce algorithm. Four lexical patterns (the lexical part) are identified among the extracted non-lattice subgraphs. Non-lattice subgraphs exhibiting such lexical patterns are often indicative of missing hierarchical relations or concepts. Each lexical pattern is associated with a potential specific type of error. …
How Leaders Market And Commercialize Healthcare Technology Innovation, Roxie Mooney, Rocky J. Dwyer Dr.
How Leaders Market And Commercialize Healthcare Technology Innovation, Roxie Mooney, Rocky J. Dwyer Dr.
Walden Faculty and Staff Publications
This study investigates what strategies technology development marketing leaders utilized to commercialize a new product innovation in the healthcare market. Analysis of data generated 3 major themes: strategies implemented during the prelaunch phase, strategies implemented during the pilot customer phase, and strategies implemented in the broader market launch phase of the CoI process. Findings from this study may contribute to maximizing commercial success and the diffusion of new product innovations in healthcare, which might lead to better patient outcomes and enhanced ways of practicing medicine.
Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image, Chulwoo Pack
Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image, Chulwoo Pack
Electronic Theses and Dissertations
Most recently developed Computer Aided Diagnosis (CAD) systems and their related research is based on medical images that are usually obtained through conventional imaging techniques such as Magnetic Resonance Imaging (MRI), x-ray mammography, and ultrasound. With the development of a new imaging technology called Microwave Tomography Imaging (MTI), it has become inevitable to develop a CAD system that can show promising performance using new format of data. The platform can have a flexibility on its input by adopting Artificial Neural Network (ANN) as a classifier. Among the various phases of CAD system, we have focused on optimizing the classification phase …
A Multi-Model Approach In Developing An Intelligent Assistant For Diagnosis Recommendation In Clinical Health Systems, Christian E. Pulmano, Ma. Regina Justina E. Estuar
A Multi-Model Approach In Developing An Intelligent Assistant For Diagnosis Recommendation In Clinical Health Systems, Christian E. Pulmano, Ma. Regina Justina E. Estuar
Department of Information Systems & Computer Science Faculty Publications
Clinical health information systems capture massive amounts of unstructured data from various health and medical facilities. This study utilizes unstructured patient clinical text data to develop an intelligent assistant that can identify possible related diagnoses based on a given text input. The approach applies a one-vs-rest binary classification technique wherein given an input text data, it is identified whether it can be positively or negatively classified for a given diagnosis. Multi-layer Feed-Forward Neural Network models were developed for each individual diagnosis case. The task of the intelligent assistant is to iterate over all the different models and return those that …