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The Role of Attention Control in Ensemble Perception in the Presence of Selection
No full textEnsemble perception is the ability to extract summary statistics (e.g., mean, variance) from the aggregations of similar objects (Whitney & Yamanashi Leib, 2018). One common task used in ensemble perception studies requires participants to select a subset of a set of items before calculating a summary statistic (e.g., average size of the red circles among blue circles). It has been assumed that adding a selection requirement to an ensemble task does not change the ability that it measures. However, a recent study (Martin et al., 2021) found that adding a selective component to a task known to measure working memory capacity can remarkably change what the task measures (either working memory capacity or attention control). Given multiple debates about the role of attention in ensemble perception, we address the assumption that the presence of selection does not alter what an ensemble perception task measures. Thus, we examined whether a type of ensemble perception task, specifically mean discrimination, measures the same ensemble perception ability regardless of the presence of selection with a latent variables approach. Our results showed that ensemble perception and attention control are correlated at the construct level and the two constructs contribute equally to predicting the performance of mean discrimination tasks. The results suggest that ensemble perception requires attention control, and that all mean discrimination tasks reflect both ensemble perception and attention control ability to the same degree
Development of Next-Generation Optical Coherence Tomography Systems for Enhancing Patient Accessibility to Ophthalmic Care
No full textVisual impairment (VI) is a global health issue that is estimated to affect 2.2 billion people worldwide and cost nearly $3 trillion USD per year. While prevalence varies across patient demographics, prevalence rates due to undiagnosed VI are significantly higher in elderly and low-income communities. Additionally, accessible screening methods are often ineffective due to inadequate technology or undetectable disease markers. Optical coherence tomography (OCT) is a promising technology that enables non-invasive 3D imaging of ophthalmic tissue and has been widely adopted in ophthalmology for its benefits over traditional diagnostic methods. However, OCT systems are bulky and expensive, which precludes their use in settings that require a portable or cost-effective device. This work aims to develop innovative technology that can reduce the size, cost and complexity of OCT systems to increase accessibility for patients in need. To this end, we first developed a compact handheld multimodal OCT probe for imaging bedridden patients that cannot be imaged on traditional benchtop systems. Next, we developed a low-cost OCT system that utilized a commercial smartphone for detection, processing and display of OCT data. The smartphone-integrated design reduces the number and cost of components in a standard OCT system that may help increase system adoption in resource-limited settings. Finally, a compact and low-cost computational spectrometer was developed to further reduce the cost and complexity of OCT systems. In summary, this thesis develops a foundation for next-generation OCT systems that can be used for screening and diagnosis of currently underserved populations
Value-based Insurance Design: An Evaluation of Insulin Cost-sharing Caps
No full textDecades of increasing diabetes prevalence and insulin costs in the U.S. have heightened attention to insulin cost-related nonadherence – impacting approximately one in five insulin-users. As of June 2024, 25 states and D.C. have capped insulin out-of-pocket costs for state-regulated health plans, but a federal cap for the privately insured remains an ongoing policy discussion. We evaluated three aims informing key questions regarding insulin out-of-pocket cost caps. The first two aims used multicarrier employer-sponsored insurance claims and a triple differences design to assess the first-year causal impact of caps (67 annually; 95th percentile: 100) may be insufficient to support the most cost-vulnerable insulin-users. The second aim evaluated the impact of caps on 30-day standardized long-acting insulin fills and found no evidence of meaningful changes. Future research should focus on cost-vulnerable subgroups, more precise outcome measures, and additional years post-implementation to capture plan renewal and product switching lag effects. The third aim used national/state health statistics and employer-sponsored insurance claims to describe what may occur under a federal cap. We estimated that almost 2 million insulin-users enrolled in ESI – including 372,000 estimated to be rationing insulin – could be newly covered by a federal insulin copay cap. A federal cap will also likely meaningfully increase health equity. Our research advances the discussion on policies to address insulin costs and related nonadherence, especially regarding a federal cap for the privately insured
Machine Learning for Multimodal Medical Data
No full textThe rapid advancement of diagnostic technologies in healthcare has heightened the demand for physicians to integrate heterogeneous yet complementary data generated during routine practice, including radiology images, pathology slides, genomic data, and clinical features. Recent progress in multi-modal learning offers new opportunities to address these challenges by facilitating the effective fusion of diverse data modalities.
This dissertation focuses on leveraging machine learning, particularly deep learning methods, to tackle challenges in multi-modal learning. It begins with an exploration of unimodal approaches, addressing segmentation and anomaly detection tasks associated with various modalities in medical domains. The core of the dissertation shifts to multi-modal learning, examining its applications in diagnosis, prognosis, and segmentation tasks that integrate multiple medical modalities. The first half proposes pipelines that combine image and non-image data for diagnostic and prognostic tasks related to gliomas and soft tissue tumors, with a focus on addressing the challenge of missing modalities during training and inference. The latter half investigates the application of multi-modal learning in medical image segmentation, highlighting the fine-tuning potential of segment-everything models using weak annotations. Additionally, language is integrated to guide pre-trained vision models, facilitating a more flexible multitask segmentation pipeline applicable to kidney pathology. In the end, the dissertation concludes with a summary of contributions and an outline of future research directions
Training Behavior Technicians to Foster Enriched Learning Contexts
No full textWhile many behavior technicians utilize natural environment teaching (NET) when delivering applied behavior analysis (ABA) therapy services, guidance is limited regarding how naturalistic intervention should be implemented. Naturalistic Developmental Behavioral Interventions (NDBIs) are a class of interventions that are behavior analytic but also incorporate developmental principles (Schreibman et al., 2015). While behavior technicians are trained on some strategies that are components of NDBIs, they are not required to be trained on developmental strategies that enrich the learning context, such as contingent imitation and linguistic mapping (Bravo, et al., 2024; Jimenez-Gomez et al., 2019), modeling (Schreibman et al., 2015), language expansions (Kaiser et al., 2000), or play expansions (Frey & Kaiser, 2011). A non-concurrent multiple baseline design was used to evaluate a cascading logic model that includes researcher training and ongoing Board Certified Behavior Analyst (BCBA)-implemented support on behavior technician (BT) use of NDBI-informed strategies designed to foster enriched learning contexts (ELC) during NET. The intervention was effective in increasing levels of play and language strategies across all three participants, increasing BT engagement across all three participants, and increasing stability in levels of engagement for two of the three child participants. The results of this study demonstrate the potential for effective training methods for recommended practices in NET that center endogenous implementers. ABA therapy centers prioritizing play-based and child-led intervention may need to consider ways to explicitly train their staff in implementing strategies that support an enriched and engaging context, which may extend beyond the bounds of current RBT Task List training requirements
CRISPR-Cas9 Targeting of the MMP13 Gene Locus Towards Treating Osteoarthritis
No full textOsteoarthritis (OA) is a degenerative joint disease that causes the continuous breakdown of cartilage that results in pain, reduced joint function, and disability. There is a need for a treatment for OA that not only aids in symptom management, but permanently stops OA progression. PTOA caused by injury, the focus of this work, is characterized by an imbalance between Matrix Metalloproteinase 13 (MMP13), which degrades type II collagen, and its endogenous inhibitor, the Tissue Inhibitor of Metalloproteinases 3 (TIMP3). We aim to develop an MMP13-targeting CRISPR-Cas9 ribonucleoprotein (RNP) and TIMP3 donor DNA template for the targeted insertion of TIMP3 into the MMP13 gene locus via homology directed repair (HDR), i.e., targeted knock-in (KI). This will create a gene circuit that produces TIMP3 under the control of the endogenous MMP13 promoter. The hypothesis is that this gene circuit will generate TIMP3 “on-demand” whenever the MMP13 promoter is activated by mechanical stimuli and other OA mediators. The results show that NHEJ-mediated MMP13 KO via CRISPR-Cas9 RNP delivery in vitro resulted in up to 95% KO that was maintained after months of subculture. The high KO efficiency was also maintained in a 3D ATDC5 aggregate model; A TIMP3 dox-inducible circuit that was stably transfected into KO (95% indel) and WT ATDC5s showed promising results of TIMP3-mediated MMP13 inhibition. An additional control using recombinant TIMP3 protein directly added to the aggregate treatment medium also showed MMP13 inhibition. Optimization of the TIMP3 DNA template (homology arm length) and in vitro transfection of both the Cas9 RNP and DNA template resulted in successful TIMP3 integration into the MMP13 genome. A mutant TIMP3 (mTIMP3) with an increased half-life in tissues was also developed and integrated into MMP13. However, neither the TIMP3 nor mTIMP3 KI cell lines showed significant MMP13 inhibition in the 3D ATDC5 aggregate model. Overall, TIMP3 was validated as a viable target to inhibit MMP13 activity and subsequent cartilage degradation in the context of PTOA, but further optimizations need to be made in the proposed gene circuit. This data demonstrates a proof-of-concept of the therapeutic potential of on-demand TIMP3 production upon MMP13 activity stimulation to permanently block PTOA progression
Quintessence Dark Energy and Cosmic String Gravitational Radiation
No full textI discuss two main topics, quintessence dark energy and cosmic string gravitational radiation. I first apply observational and theoretical constraints to thawing quintessence dark energy models to determine the viable parameter spaces for λ=|V'/V| and K=√(1-(4V''(ϕ_i))/(3V(ϕ_i))), which was determined to be λ≈(0.1,1) and K∈( √(7/3),5 ), respectively. This region was found to be within observational limits without being finely tuned and allowed by the refined de Sitter conjecture, which is contrary to previous results which used different priors. Therefore, I conclude that viability of quintessence models is highly dependent on chosen priors. I also produced observational constraints on inflection point quintessence potentials of the form V(ϕ)=V_0+V_3 ϕ^3 (similar results are expected for other inflection point models). It was found that, aside from typical asymptotic de Sitter evolution, there is a permitted parameter space that would result in a transient period of acceleration. Regarding gravitational waves, the initial undecayed power spectrum P_n for Garfinkle-Vachaspati (GV) loops was calculated to be on the order of n^(-2) (1+ln(n)) for large values of n. This logarithmic correction differs from the previously-assumed power law of n^(-2) for kink-kink collisions. Decayed GV loops, to a first-order approximation, with small opening angles have even slightly more power at larger modes, which will have a small but nonzero effect on predictions for the stochastic background from cosmic strings. Finally, I also studied the waveforms of the GV loop gravitational radiation, and discovered that, although the period decreases, the waveform remains similar to the undecayed loop up to the applicability of the approximation used for the decay for larger opening angles ( α>π/4 ), but for smaller opening angles, the waveform becomes distorted and therefore unique, which should be noted in periodic searches for GV loops
Development of a Quarterly Scorecard for the Adult Respiratory ECMO Program at VUMC
No full textSchool of Nursing Doctor of Nursing Practice Program ProjectPURPOSE:
This project aimed to enhance the quality of Extracorporeal Membrane Oxygenation (ECMO) care at Vanderbilt University Medical Center (VUMC) by developing a quarterly quality and performance scorecard for the adult respiratory ECMO program. Despite VUMC's comprehensive internal quality database, utilization of quality metrics was minimal. Following the Extracorporeal Life Support Organization's (ELSO) guidelines, this initiative sought to improve our program evaluation.
METHODS:
Development of the ECMO scorecard involved collaborative drafting with key stakeholders during the Fall of 2023. Utilizing data from VUMC's quality assurance database, the scorecard was refined and disseminated to the medical intensive care unit (MICU) advanced practice provider (APP) team in January 2024. Implementation outcomes were measured using the Acceptability of Intervention Measure (AIM) and Intervention Appropriateness Measure (IAM), with higher scores indicating greater acceptability and appropriateness.
RESULTS:
The scorecard was finalized and distributed to 16 MICU APPs, achieving a 62.5% survey response rate. The feedback indicated high acceptability (AIM mean score: 4.38) and appropriateness (IAM mean score: 4.5) of the ECMO scorecard among respondents.
IMPLICATIONS FOR PRACTICE:
The successful development of the ECMO scorecard demonstrates its potential to improve clinical practice by providing a valuable tool for quality assessment and improvement. The positive reception among providers supports the utility of similar data analytics tools in enhancing patient care. Future directions include expanding the scorecard with benchmarking data and integrating dynamic access features through REDCap
Ultra-Low-Overhead Arbitrary-Waveform Generation as a Circuit Macro: Augmenting the Characterization of Radiation-Induced Transient Effects in Highly Scaled Integrated Circuits
No full textArbitrary waveform generators (AWGs) are not typically feasible as subsystems on integrated circuits due to their size and complexity, but they are versatile circuits that are broadly useful. The purpose of this work is to show that by prioritizing minimal overhead and designing for targeted performance, as necessary for the application, it is possible to create a reusable on-chip AWG circuit macro in a small form factor. To support this claim, details and results are provided for a proof-of-concept implementation in a 45nm partially depleted silicon-on-insulator process. The presented design is able to achieve a small size by eliminating the complicated calibration and filtering circuitry commonly used in contemporary designs, instead relying on intrinsic accuracy of the base circuits. The reliability and accuracy of the AWG are driven by careful design down to the layout level, including the development of a variant of the traditional common-centroid layout technique called distributed-centroid layouts (DCL), which addresses the importance of bias circuitry in mitigating process-induced mismatch. A custom simulation workflow was developed to investigate the effectiveness of this technique at the circuit level as compared to other designs from the literature. The proof-of-concept circuit was designed to improve the characterization of radiation-induced transient effects in highly scaled integrated circuits by providing built-in self-test and hardware-emulation capabilities to a custom photocurrent measurement circuit (PMC). Details of this specific application are explored in detail, along with experimental measurements made using flash x-ray and pulsed laser sources. Alternative AWG designs that might benefit a broader application space beyond radiation effects are also provided
Ultra-Low-Overhead Arbitrary-Waveform Generation as a Circuit Macro: Augmenting the Characterization of Radiation-Induced Transient Effects in Highly Scaled Integrated Circuits
No full textArbitrary waveform generators (AWGs) are not typically feasible as subsystems on integrated circuits due to their size and complexity, but they are versatile circuits that are broadly useful. The purpose of this work is to show that by prioritizing minimal overhead and designing for targeted performance, as necessary for the application, it is possible to create a reusable on-chip AWG circuit macro in a small form factor. To support this claim, details and results are provided for a proof-of-concept implementation in a 45nm partially depleted silicon-on-insulator process. The presented design is able to achieve a small size by eliminating the complicated calibration and filtering circuitry commonly used in contemporary designs, instead relying on intrinsic accuracy of the base circuits. The reliability and accuracy of the AWG are driven by careful design down to the layout level, including the development of a variant of the traditional common-centroid layout technique called distributed-centroid layouts (DCL), which addresses the importance of bias circuitry in mitigating process-induced mismatch. A custom simulation workflow was developed to investigate the effectiveness of this technique at the circuit level as compared to other designs from the literature. The proof-of-concept circuit was designed to improve the characterization of radiation-induced transient effects in highly scaled integrated circuits by providing built-in self-test and hardware-emulation capabilities to a custom photocurrent measurement circuit (PMC). Details of this specific application are explored in detail, along with experimental measurements made using flash x-ray and pulsed laser sources. Alternative AWG designs that might benefit a broader application space beyond radiation effects are also provided