Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 45 for “"Healthcare Applications"”.
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Geometric Deep Learning for Healthcare Applications
This thesis explores the application of Graph Neural Networks (GNNs), a subset of Geometric Deep Learning methods, for medical image analysis and causal structure learning. Tracking the progression of pathologies in chest radiography poses several challenges in anatomical motion estimation and …
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Soft Electronics and Sensors for Wearable Healthcare Applications
… reliable sensors for wearable health monitoring applications.</p><p>More specifically, we have studied the silver nanoparticles (AgNPs) inkjet-printed on a polydimethylsiloxane (PDMS) substrate that offers great pressure sensitivity for aterial pulse monitoring. In addition, we have investigated …
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Multiphysics Modeling Of Devices For Whole Organ Healthcare Applications
… manufacturing, and modeling of novel organ healthcare devices. Specifically, we applied template engineering and structured-light scanning techniques to capture the 3D topographical information for whole organ systems. Sequentially, we developed multiphysics models for understanding the …
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Portable acquisition and interpretation of EEG for neonatal healthcare applications
… are optimised for use in resource-constrained applications and platforms. To date, minimal consideration is given to the regulatory and commercial requirements when developing medical devices in academia. This introduces a barrier to bringing academic innovation through to clinical adoption. A …
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A novel approach to protecting mobile healthcare applications in mobile cloud
In recent years there has been a shift in the devices that people use to do their computing. Of particular import has been the movement in the computing landscape towards mobile devices. As would be expected, the proliferation of mobile devices has led to an increase in their being a target for …
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Evaluating Differences in GPT-4 Treatment by Gender in Healthcare Applications
LLMs already permeate medical settings, supporting patient messaging, medical scribing, and chatbots. While prior work has examined bias in medical LLMs, few studies focus on realistic use cases or analyze the source of the bias. To assess whether medical LLMs exhibit differential performance by …
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A low power, reconfigurable fabric body area network for healthcare applications
Body Area Networks (BANs) are gaining prominence for their capability to revolutionize medical monitoring, diagnosis and treatment. This thesis describes a BAN that uses conductive fabrics (e-textiles) worn by the user to act as a power distribution and data communication network to sensors on the …
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Integrating Optimization and Modern Machine Learning: Theory, Computation, and Healthcare Applications
… theory, computational tools, and diverse applications. In Chapter 1, we extend state-of-the-art tools from robust optimization to non-convex and non-concave settings, allowing us to generate neural networks that are robust against input perturbations. In Chapter 2, we develop a holistic …
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Non-invasive wearable sensing systems for continuous health monitoring and long-term behavior modeling
Deploying new healthcare technologies for proactive health and elder care will become a major priority over the next decade, as medical care systems worldwide become strained by the aging populations. This thesis presents LiveNet, a distributed mobile system based on low-cost commodity hardware …
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Design and Development of a Mobile Motion Capture Suite for Advancing Technology Adoption
… including filmmaking, manufacturing, sports, and healthcare. Yet, the high cost and complexity of existing precise MoCap systems can make them inaccessible to many people. In addressing this accessibility problem, the Lab-in-a-Box (LabX) project was initiated within MIT’s Center for Clinical and …
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Structured machine learning for dynamical systems in healthcare
Modelling the evolution of dynamical systems in healthcare is an important research area with many applications, ranging from determining the optimal duration of medical treatments to controlling the spread of an epidemic. There has been two dominate approaches for modelling dynamical systems. The …
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Classification of Clinical Tweets Using Apache Mahout
There is an increasing amount of healthcare related data available on Twitter. Due to Twitter’s popularity, every day large amount of clinical tweets are posted on this microblogging service platform. One interesting problem we face today is the classification of clinical tweets so that the …
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Benchmarking Reinforcement Learning and Off Policy Evaluation for Medical Decision Making
<p>Healthcare applications pose significant challenges to existing Reinforcement Learning (RL) methods due to implementation risks, low data availability, short treatment episodes, sparse re[1]wards, partial observations, and heterogeneous treatment effects (HTE). Despite significant interest in …
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Activity recognition with end-user sensor installation in the home
… not only in home-based proactive and preventive healthcare applications, but also in learning environments, security systems, and a variety of human-computer interfaces.
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Guayule plant extracts as binder modifiers in flexible (asphalt) pavement mixtures
… Yulex produced hypoallergenic guayule latex for healthcare applications using a water-based extraction method. Of the many guayule-based materials investigated, an acetone-extractable, residual resin in the dried latex was shown to be an effective recycling agent for FPMs with high contents of …
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In-sensor information processing for resource-limited platforms on flexible epidermal substrates
… performance and cost. A large class of these healthcare applications require digital signal processing algorithms to be implemented with strict resources, such as energy and silicon area. Shrinking technology nodes produce both higher computing performance and energy efficiency. However, …
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Antifouling and Antithrombogenic Ultrathin Surface Chemistry for Bioanalytical and Biomedical Applications
… chemistry, for bioanalytical and biomedical healthcare applications. Surface modification also has the advantage of being straightforward, rapid and inexpensive.One primary objective was to engineer biosensors capable of selectively and sensitively detecting target analytes in real-world …
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RF SENSORS FOR MEDICAL AND CYBER-PHYSICAL INTELLIGENCE
… comfort and convenience to enable many healthcare applications, especially for at-home continuous diagnosis and prognosis, with less reliance on subjective self report. My research utilized machine-learning (ML) algorithms that can take the physiological data from our sensors to provide …
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Biomimetic Biomechanical Sensors for Intelligent Wearable Interfaces
… with high fidelity can unlock transformative applications in silent communication, healthcare monitoring, and immersive human-machine interaction. However, current biomechanical sensors remain limited in sensitivity within small strain range, omnidirectional responsiveness, spatiotemporal …
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Interpretability and Debugging for Distributed Privacy Preserving Machine Learning
… raw client data (e.g., Siri, Alexa, and healthcare applications). Centralized machine learning benefits from rich debugging and interpretability techniques enabled by transparent access to training data. However, FL removes this transparency, rendering traditional techniques ineffective …
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