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- Creator:
- Irani, Sanaya , Tolia, Sangini, Finks, Jonathan, and Sandhu, Gurjit
- Description:
- Program Description DoT was founded in 2012 with a mission to increase diversity amongst medical professionals by preparing students from underrepresented communities in Detroit to successfully pursue careers in healthcare. Our program builds on a partnership between Cass Technical High School (CTHS) and the University of Michigan Medical School (UMMS). The CTHS student body is reflective of the Detroit population with more than 80% of students identifying with racial and ethnic minority backgrounds. Students with an interest in healthcare apply for the program as ninth graders. In recent years, the program has received over 60 applications for approximately 30 positions in each grade. DoT’s unique strength lies in its longitudinal structure. There are three branches of the program – Foundations (ninth and tenth grade), Rising (eleventh and twelfth grade) and Succeed (undergraduate). Ninth graders start out in DoT Foundations. Each student is paired with a first-year medical student mentor at UMMS for the entire academic year. DoT students travel to UMMS every month for a visit day, with activities designed to give students hands-on experiences in healthcare, such as suturing and ultrasound skills in the simulation center, and clinical shadowing. Students then meet with their medical student mentor over lunch. The latter part of the day is dedicated to working on their capstone projects. For the capstone projects, students work in small teams led by medical student leaders to identify a community health issue, partner with a local organization, and present their proposed solutions at a formal symposium at the end of the year. , Transition to Virtual Programming In light of the recent COVID-19 pandemic, a growing number of universities cancelled all campus events including those of pipeline programs. We felt that our programming offered an important service to our students that would be greatly missed, so our team worked to quickly create and implement a virtual program. We ensured that each of our students had access to technology at home and those who did not were offered scholarships. During our introductory student session and new parent meeting, our leadership team discussed how to set up a Gmail email address for weekly communications and taught the students how to use Zoom, Google Drive, Google Docs and Google Sheets for online learning collaboration. For the virtual Foundations program, we offered 1-hour seminars each month, where a physician was invited to give a 30-minute presentation about different organ systems, followed by a 30-minute case-based session where students worked with medical student mentors to apply their new knowledge. We also created novel sessions such as “The Path to College and Medical School” and collaborated with members of the Black Medical Association (BMA) and Latin American and Native American Medical Association (LANAMA) to host a panel session where students could learn from medical students who identified as URiM. For the mentorship aspect, we created “pods” of Foundations, Rising, and Succeed students along with medical student and physician mentors. The Foundations students and mentors met every month for an hour on Zoom, a virtual communication platform, to work on their Capstone project. Rising and Succeed students joined the group for three full-pod meetings. The goal was to increase near-peer mentorship and connections between DoT students at all levels. , and Study Population Due to the virtual nature of the 2020-2021 program, we accepted 100% of 9th grade applicants from CTHS. We also expanded our reach to a new school, The School at Marygrove (TSM), which is also located in Detroit, Michigan. TSM is involved in the Detroit-20 Partnership with the University of Michigan College of Education and includes a novel three-year residency program for novice teachers. During the 2020-2021 school year, 108 students participated in the Foundations programming with 72 of them being 9th graders and 36 being 10th graders. The students were mostly from CTHS with 12 students out of the 108 total being from TSM. Students were predominantly from an African American/Black racial background (68.4% from N=98 respondents). The students were representative of their respective schools. The majority of students at CTHS identify as black, come from low-income homes, and have variable levels of parental education.
- Keyword:
- pipeline program, Underrepresented in medicine, Mentorship, Medical education, and COVID-19
- Discipline:
- Health Sciences
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- Creator:
- Alvarado, Roman, Scheven, Ulrich M., and Meiners, Jens-Christian
- Description:
- MRI raw data Image analysis script Raw pressure and vitals data
- Keyword:
- Decompression Sickness
- Citation to related publication:
- Alvarado R, Scheven U. M, Meiners, J. C.: Real-time Imaging of Decompression Gas Bubble Growth in the Spinal Cord of Live Rats, Magnetic Resonance in Medicine, 2024, in press
- Discipline:
- Health Sciences
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- Creator:
- Bautista-Arredondo, Luis F., Muñoz-Rocha, T. Verenice, Figueroa, José L., Téllez-Rojo, Martha M., Torres-Olascoaga, Libni A., Cantoral, Alejandra, Arboleda-Merino, Laura C., Leung, Cindy, Peterson, Karen E., and Lamadrid-Figueroa, Héctor
- Description:
- Data was collected from participants of the Early Life Exposures in Mexico to ENvironmental Toxicants (ELEMENT) study, which consists of three sequentially-enrolled birth cohorts of pregnant women. Research protocols of this study were approved by the Institutional Review Board at University of Michigan and the Mexico National Institute of Public Health. We obtained informed consent from study participants prior to enrollment.
- Keyword:
- Food Insecurity, COVID-19 Pandemic, Mexico, Cohort
- Citation to related publication:
- Bautista-Arredondo LF, Verenice Muñoz-Rocha T, Figueroa JL, Téllez-Rojo MM, Torres-Olascoaga LA, Cantoral A, Arboleda-Merino L, Leung L, Peterson KE, and Lamadrid-Figueroa H. A surge in food insecurity during the COVID-19 pandemic in a cohort in Mexico City. 2022. Article in process of publication.
- Discipline:
- Health Sciences
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- 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
-
- Creator:
- Malyarenko, Dariya, Chenevert, Thomas L, Heist, Kevin, Bonham, Christopher, and Ross, Brian
- Description:
- The imaging data was used to measure repeatability and temporal trends of quantitative imaging biomarkers of myelofibrosis in bone marrow based on apparent diffusion coefficient, fat fraction and magnetization transfer ratio. The dataset consists of time series of the MRI Meta-image-header (MHD) images of wild type and diseased mice combined by the imaging time point. The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. Each time point image archive is structured with a directory tree that contains ./././"mouseID"/"scan-date"/"acquisition type"/
- Keyword:
- murine tibia MRI, bone marrow imaging, apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), magnetization transfer ratio (MTR), and pre-clinical model of myelofibrosis
- Citation to related publication:
- Ross BD, Malyarenko D, Heist K, Amouzandeh G, Jang Y, Bonham CA, Amirfazli C, Luker GD, Chenevert TL. Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model. Tomography. 2023 Feb 28;9(2):552-566. doi: 10.3390/tomography9020045. PMID: 36961004; PMCID: PMC10037563.
- Discipline:
- Health Sciences
-
- Creator:
- Samuel, Sara M, Wilson, Diane L, and Fleming, Emily K
- Description:
- The International Committee of Medical Journal Editors (ICMJE) requires researchers to post individual participant data (IPD) plans for interventional clinical trials with registration in order to be eligible for publication in its member journals. This study looked at how researchers interpret the ICMJE requirements and the related prompts for information used by ClinicalTrials.gov. This data consists of the analyzed contents of the IPD plans that researchers at the University of Michigan (U-M) submitted with trial registrations for the first 27 months that the 2019 requirement was in effect.
- Keyword:
- research data sharing, research data policy, research data, clinical trials, ClinicalTrials.gov, individual participant data, IPD, data sharing plan, and compliance
- Citation to related publication:
- Samuel, S. M. & Wilson, D. L. & Fleming, E., (2023) “Evaluating individual participant data plans for ICMJE compliance: A case study at University of Michigan”, Journal of the Society for Clinical Data Management 3(4). doi: https://doi.org/10.47912/jscdm.257
- Discipline:
- Health Sciences, Social Sciences, and General Information Sources
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- Creator:
- Lumeng, Julie C
- Description:
- Infant eating behavior is likely driven not only by hunger and satiety reflective of caloric need, but also by the reward value of food. The reward value of food can be understood in terms of wanting, liking, and salience. Little is understood about infant response to the reward value of food, or its predictors, particularly prenatally. This project sought to understand whether prenatal factors during pregnancy predict infant reward response to food, as measured by questionnaires in early infancy.
- Keyword:
- wanting, liking, salience, infancy, eating, growth, and prenatal
- Discipline:
- Health Sciences
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- Creator:
- Cevidanes, Lucia
- Description:
- Image Pre-Processing To allow reliable detection and comparison of changes between several individuals or within the same individual at different time points, before extracting the quantitative bone texture/morphometry features, all hr-CBCT scans were pre-processed using validated protocols. Extraction of Trabecular Bone Texture-based and Morphometry Imaging Features Using the “crop-volume” tool in 3D Slicer, a rectangular shaped volume of interest (VOI) was cropped from the trabecular bone in the mandibular condyles and the articular fossa. Then, using the average minimum and maximum intensity values of all VOIs, we standardized the grey level intensities of the VOIs to eliminate inaccuracies of textural features calculation and possible dependency on the global characteristics of the images. Lastly, imaging markers were extracted from the standardized VOIs using “BoneTexture” module in 3D-slicer. Measurement of the 3D Articular Joint Space To assess the progression/improvement of osteoarthritic changes in the affected individuals, we measured the 3D superior joint space. We pre-labelled two landmarks in the sagittal view of the oriented CBCT scans: on the most superior point of the condyle and on the opposing surface of the articular fossa. To avoid biasing the landmarks’ placements, pre-labelling was performed simultaneously on T1 and T2 scans, using two independent windows in ITK-SNAP. After the volumetric reconstruction of the identified landmarks, linear measurements were obtained in millimeters using the Q3DC tool in 3D Slicer. Three-dimensional Shape Analyses and Quantification of Remodeling in the Condyles SPHARM-PDM software was used to compute the correspondence across 4002 surface points among all condyles. The output point-based models displayed color-coded maps that enabled visual evaluation of consistent parametrization of all condyles. An average condyle shape for the TMJ OA and control groups was calculated through propagation of original surface point correspondences across all stages of deformations and averaging the condyle surface meshes. For visualization of the 3D qualitative changes of the average models within the same group at different time points or among different groups, semi-transparent overlays were created using 3D Slicer software. The vector differences were presented on the condyle surfaces, scaled according to the magnitude of difference, and pointing towards the direction of bone change. For quantification of remodeling in the condyles, calculation of signed distances across condyles surface meshes reflected the quantitative bone changes in the TMJ OA and control samples. To quantify regional bone changes across the lateral and anterior surfaces of the condyles, we used the Pick ‘n Paint tool in 3D Slicer to propagate regional surface points to the corresponding regions of shapes across all subjects and time points.
- Keyword:
- Degenerative joint disease, Temporomandibular joint osteoarthritis, TMJ OA, Machine learning, Prognosis
- Discipline:
- Health Sciences
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- Creator:
- Lori, Jody R., Moyer, Cheryl, Lockhart, Nancy, Zielinski, Ruth E., Kukula, Vida, Apetorgbor, Veronica, Awini, Elizabeth, Badu-Gyan, Georgina, and Williams, John
- Description:
- GRAND is a five-year, cluster randomized controlled trial. The study is registered on ClinicalTrials.gov, [ID#: NCT04033003] and is a collaboration between University of Michigan in the United States and the Dodowa Health Research Center in Ghana. , The study setting for GRAND is four districts (Akwapim North, Yilo Krobo, Nsawam-Adoagyiri, and Lower Manya Krobo) within the Eastern Region of Ghana. Health facilities were selected based the number ANC registrants per month and average gestational age of women at registration in each facility., and Facilities were then matched based on facility type, district, and number of monthly ANC registrants. A cluster randomized controlled trial was conducted in 14 facilities in four districts of the Eastern Region of Ghana. Health facilities were randomized using a matched pairs design; each pair was similar in the number of deliveries and average gestational age of the women at enrollment in antenatal care. The locations of the facilities were far enough apart to avoid cross-group contamination. In each pair of facilities, one was randomly assigned to the intervention (G-ANC) and the other to the control (I-ANC). Recruitment began July 2019 and ended when enrollment targets were met. Data collection ended July 2023 when data collection was complete.
- Keyword:
- Antenatal care, Ghana, and Maternal health
- Citation to related publication:
- Lori, J., Kukula, V., Liu, L. et al. Improving health literacy through group antenatal care: results from a cluster randomized controlled trial in Ghana. BMC Pregnancy Childbirth 24, 37 (2024). https://doi.org/10.1186/s12884-023-06224-x
- Discipline:
- International Studies and Health Sciences
-
- Creator:
- Rana, Gurpreet K., Reynolds, Christopher W., Rha, Jennifer Y., Lenselink, Allison M., Asokumar, Dhanya, Zebib, Laura, Giacona, Francesca L. , Islam, Nowshin N., Kannikeswaran, Sanjana, Manuel, Kara, Cheung, Allison, Marzoughi, Maedeh , and Heisler, Michele
- Description:
- The search data supports a literature review project on "Innovative strategies and implementation science approaches for health delivery among migrants in humanitarian settings". The data included in the dataset are the complete search strategies (rtf file) and the exported results of all citations from all databases (ris file) after removal of duplicate citations.
- Keyword:
- humanitarian setting, migrant, forced displacement , health delivery, implementation science, and scoping review
- Discipline:
- Health Sciences