Search Constraints
Number of results to display per page
View results as:
Search Results
-
- Creator:
- Gharzai, Laila A, Green, Michael D, Griffith, Kent A, and Jolly, Shruti
- Description:
- Three sensitivity analyses were performed. First, a second matching step was performed in which two controls were selected for each case, where possible using a nearest neighbor and caliper metric. Controls needed to have propensity scores within 0.1 of the case to be selected. Thirty-eight of the 39 cases had at least one control using this method and for 36 cases two controls could be selected. The average difference between case and control propensity adjuvant RT was 0.008 (range 0.00003-0.095). A second sensitivity analysis was performed to guard against immortal time bias. In order to mitigate the possibility of this effect, cases known not to have undergone adjuvant RT have been screened for suitable follow-up without a recurrence (local or regional recurrence, metastatic failure, and/or death) to ensure that if adjuvant RT had been prescribed as part of the multi-modality treatment regimen, that it would have been initiated. Three months was selected as the mandatory follow-up time. One to one matching was carried out and all 39 cases were matched to a control. A third sensitivity analysis was performed to account for stage migration seen in control patients that presented to the University of Michigan with more advanced disease. Patients that underwent adjuvant radiation were matched one to one with control group patients who did not receive adjuvant radiation, and who had the same stage at diagnosis as compared to stage at University of Michigan presentation.
- Keyword:
- adenocortical carcinoma and English
- Discipline:
- Health Sciences
-
- Creator:
- Batterman, Stuart; University of Michigan
- Description:
- We evaluated PM levels at the Agbogbloshie e-waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations. This monitoring forms part of the West Africa-Michigan Charter II for GEOHealth cohort study, which is analyzing occupational exposures and health risks at this site.
- Keyword:
- Air pollution, particulate matter, e-waste, Fires, and monitoring
- Citation to related publication:
- Kwarteng, L., Baiden, E. A., Fobil, J., Arko-Mensah, J., Robins, T., & Batterman, S. (2020). Air Quality Impacts at an E-Waste Site in Ghana Using Flexible, Moderate-Cost and Quality-Assured Measurements. GeoHealth, 4(8), e2020GH000247. https://doi.org/10.1029/2020GH000247
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- George De la Rosa, Mery Vet, Patel, Dipali, McCann, Marc R., Stringer, Kathleen A., and Rosania, Gus R.
- Description:
- These data were produced from a study that employed a database strategy to identify candidate mitochondrial metabolites that could be clinically useful to identify individuals at increased risk of mitochondrial-related ADRs. The main candidate metabolite identified by the database strategy was evaluated using a mouse model of mitochondrial drug toxicity. These findings are described in our manuscript: Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity. Data reported was supported by funding from the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (NIH) under award numbers R01GM127787 (GRR) & R35GM136312 (KAS).
- Keyword:
- mitochondrial-realted metabolites, adverse drug reactions, and mitochondrial drug toxicity
- Discipline:
- Health Sciences
-
- Creator:
- Pedde, Meredith
- Description:
- In this study, we took advantage of the randomized allocation of the US EPA's funding for school bus replacements and retrofits to causally assess the impacts of upgrading buses on student attendance through the EPA’s national School Bus Rebate Program. Specifically, we used classical intent-to-treat analyses for randomized controlled trials to compare the change in school district level attendance rates after vs before the 2012 through 2017 lotteries by funding selection status . We used overall district attendance rates since rates were not available for only school-bus riders.
- Keyword:
- School Bus Emissions, Diesel Air Pollution, and School Attendance
- Citation to related publication:
- Pedde, M., Szpiro, A., Hirth, R. et al. Randomized design evidence of the attendance benefits of the EPA School Bus Rebate Program. Nat Sustain (2023). https://doi.org/10.1038/s41893-023-01088-7
- Discipline:
- Health Sciences
-
- Creator:
- Pedde, Meredith
- Description:
- In this study, we took advantage of the randomized allocation of the US EPA's funding for school bus replacements and retrofits to causally assess the impacts of upgrading buses on students' educational performance through the EPA’s national School Bus Rebate Program. Specifically, we used classical intent-to-treat analyses for randomized controlled trials to compare the change in school district level reading and language arts and math standardized test scores after vs before the 2012 through 2016 lotteries by funding selection status . We used overall district average standardized test scores since rates were not available for only school-bus riders.
- Keyword:
- School Bus Emissions, Diesel Air Pollution, and Student standardized testing
- Citation to related publication:
- Pedde, M., Szpiro, A., Hirth, R., Adar, S. School Bus Rebate Program and Student Educational Performance Test Scores. JAMA Network Open (2024). https://doi.org/10.1001/jamanetworkopen.2024.3121
- Discipline:
- Health Sciences
-
- Creator:
- Kue, Jessie and Meurer, William
- Description:
- NHAMCS is an annual survey of emergency department visits. and SAS programs are required to read this data.
- Keyword:
- emergency department and hypertension
- Citation to related publication:
- Kue, J., & Meurer, W. (2020). Association between blood pressure, race, ethnicity and likelihood of admission to the hospital from United States emergency departments – A cross sectional study. F1000Research, 9, 1116. https://doi.org/10.12688/f1000research.24757.1
- Discipline:
- Health Sciences
-
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Meurer, William
- Description:
- Full analytical dataset with labels in SPSS
- Keyword:
- Diagnostic testing
- Discipline:
- Health Sciences
-
- Creator:
- Umberfield, Elizabeth, Ford, Kathleen, Stansbury, Cooper, and Harris, Marcelline R.
- Description:
- Research Overview: This dataset is clinical consent forms, collected as part of Dr. Elizabeth Umberfield's dissertation research of at the University of Michigan. 134 consent forms are used in the analysis, 102 of which are shared here (not all are shared due to data protection agreements with participating sites). The research aimed to enable representation of clinical consent forms and their permissions within the Informed Consent Ontology. These efforts were supported by the Rackham Graduate Student Research Grant, and Dr. Umberfield's doctoral training was supported by the Robert Wood Johnson Foundation Future of Nursing Scholars Program.
- Keyword:
- Consent, Consent Form, Informed Consent, Health Care, and Healthcare
- Citation to related publication:
- Umberfield, E., Jiang, Y., Fenton, S., Stansbury, C., Ford, K., Crist, K., Kardia, S., Thomer, A., & Harris, M. R. (In Press). Lessons Learned for Identifying and Annotating Permissions in Clinical Consents. Applied Clinical Informatics. and Umberfield, E., Stansbury, C., Ford, K., Jiang, Y., Kardia, S. L. R., Thomer, A., & Harris, M. R. (Under Review). Evaluating and Extending the Informed Consent Ontology for Representing Permissions from the Clinical Domain.
- Discipline:
- Health Sciences
-
- Creator:
- Dariya, Malyarenko, Tariq, Humera, Kushwaha, Aman, Mourad, Rami, Heist, Kevin, Chenevert, Thomas L, Ross, Brian D, Chen, Heang-Ping, and Hadjiiski, Lubomir
- Description:
- The 3D GRE MRI data for murine model of myelofbifrosis with expert segmentations of mouse tibia was used to train Attention UNET model to automate bone marrow segmentation for measurements of imaging biomarkers. This dataset consists of three archives: (1) containing the source MRI images in Meta-image-header (MHD) format with resulting segmentation labels by two experts and four UNET models with different training scenarios; (2) corresponding training models; and (3) deep-learning (DL)-based segmentation tools for application to future murine tibia MRI data. and The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. The image archive is structured with a directory tree that contains \"mouseID"\"scan-date"\"segmentaion-scenario"\. The "training model" archive containes DL-model labeled by the data subset, and "deployment" archive containes the DL-segmentation software.
- Keyword:
- deep-learning segmentation, preclinical MRI, murine tibia, and mouse model of myelofibrosis
- Citation to related publication:
- Kushwaha A, Mourad RF, Heist K, Tariq H, Chan HP, Ross BD, Chenevert TL, Malyarenko D, Hadjiiski LM. Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography. 2023 Mar 7;9(2):589-602. doi: 10.3390/tomography9020048. PMID: 36961007; PMCID: PMC10037585. and https://github.com/dumichgh/MFJK1_Segmentation_MHDs
- Discipline:
- Health Sciences