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.
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Showing 1 to 20 of 113 for “"Medical Data"”.
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Learning classifiers from medical data
… techniques to discover classifiers from a database of medical data. Through the use of two software programs, C5.0 and SVMLight, we analyzed a database of 150 patients who had been operated on by Dr. David Rattner of the Massachusetts General Hospital. C5.0 is an algorithm that learns …
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Visualizing medical data using direct volume rendering
… used to display large-scale three dimensional datasets that are generated from physical measurement or computational simulation. The objective of volume rendering is to produce two dimensional images that allow the viewer to easily interpret the three dimensional nature of the dataset. This …
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Modeling Human-Informed Variables in Medical Data
… Age of Information and Artificial Intelligence, data plays a major role in analyzing and understanding underlying trends and patterns as well as informing processes and operations. Medical data often captures information beyond mere patient conditions and state, but also human behavioral aspects …
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Statistical methods for longitudinal medical data with applications
… this thesis, we discuss the use of longitudinal data in biostatistics and their analysis, focusing on three specific real cases of study. Longitudinal data refer to collections of repeated measurements of specific variables of interest at multiple time points. Their analysis offers many …
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Designing object-oriented interfaces for medical data repositories
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
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Volumetric rendering for holographic display of medical data
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1988.
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Learning Representations for Limited and Heterogeneous Medical Data
Data insufficiency and heterogeneity are challenges of representation learning for machine learning in medicine due to the diversity of medical data and the expense of data collection and annotation. To learn generalizable representations from such limited and heterogeneous medical data, we aim to …
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Hypothesis testing and causal inference with heterogeneous medical data
Learning from data which associations hold and are likely to hold in the future is a fundamental part of scientific discovery. With increasingly heterogeneous data collection practices, exemplified by passively collected electronic health records or high-dimensional genetic data with only few …
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Perceptual depth cues in support of medical data visualisation
… provide clinically useful visualisations of the data produced by an X-ray /CT scanner. Specifically, it examines the use of perceptual depth cues (PDCs) and perceptual depth cue theory to create effective visualisations. Two visualisation systems are explored: one to display X-ray data and the …
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Privacy-Preserving Synthetic Medical Data Generation with Deep Learning
… Language Processing. However, the utilization of data-driven methods in healthcare raises privacy concerns, which creates limitations for collaborative research. A remedy to this problem is to generate and employ synthetic data to address privacy concerns. Existing methods for artificial data …
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Feature Selection for High-risk Pattern Discovery in Medical Data
… industry, substantial amounts of electronic medical data have been accumulated. Mining such data could provide useful knowledge for health care provider to improve the quality of the service been delivered. One application is to identify the patients at high-risk of severe chronic or …
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Learning with less: machine learning techniques for scarce medical data
… has demonstrated significant potential in medical applications. However, its success often depends on large, clean datasets, a condition rarely met in real-world medical settings, where data is often scarce, incomplete, or expensive. This affects medical machine learning throughout the …
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Variable selection in logistic regression, with special application to medical data
… proposed in the statistical, epidemiological and medical literature for prediction and estimation problems in logistic regression will be described. The procedures will be applied to medical data sets. On the basis of the literature review as well as the applications to examples, strengths and …
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MedRec : blockchain for medical data access, permission management and trend analysis
… of the healthcare industry to implement novel data sharing approaches. We now face a critical need for such innovation, as personalization and data science prompt patients to engage in the details of their healthcare and restore agency over their medical data. This thesis proposes MedRec: a …
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Medical data mining : improving information accessibility using online patient drug reviews
… language model for speech recognition in the medical domain, with transcribed data on sample patient comments collected with Amazon Mechanical Turk. Our findings show that patient-reported drug experiences have great potential to empower consumers to make more informed decisions about medical …
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Cross-correlations in medical data: theory, algorithms, and applications in disease analytics
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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The Kooshball algorithm--a ray tracing region growing algorithm for medical data
Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1994.
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Attacks on medical data and centralized social platforms: PU learning and graphical inference
Embargo set by: Seth Robbins for item 121048 Lift date: 2024-01-12T22:35:30Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system
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Learning guided associations of phenotypes and genotypes using high-order multi-modal representations of longitudinal medical data
… be affected by AD by 2050. With availability of medical devices during the past decades, we now have access to electronic medical records containing a varied set of clinical data coming from multiple sources, including brain imaging scans from different modalities, acquired over time in a …
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