An emphasis on the psychosocial elements of living with diseases such as breast ラーメンベット 評判 may seem uncommon in engineering. But Mia K. Markey, biomedical engineering professor in the ラーメンベット 禁止ゲーム of Engineering, is dedicated to designing decision-support systems for patients, aiming to help enhance their quality of life post-treatment.
Her research approach is firmly rooted in finding data-driven solutions for ラーメンベット 評判 diagnosis and treatment. Her most recent work is focused on creating a cost-effective computational decision-making aid for breast ラーメンベット 評判 survivors.
Markey is acutely aware that every number generated by the algorithms and datasets she relies on for her work represents a human being suffering from a terrifying disease.
"ラーメンベット 評判 robs us of our days,” she said. “The thievery can come as a direct reduction in lifespan. But the days stolen by suffering are just as lost to us. My research is important to me because I believe it will help improve the quality of people’s lives.”
Her and her team’s recent study focuses on the welfare of patients considering breast reconstruction surgery following breast ラーメンベット 評判 treatment. They found that women wish their doctors gave them more information on all potential outcomes before making a decision on which procedure was right for them. The study was presented this month by Krista Nicklaus, one of Markey’s Ph.D. students, at the Biomedical Engineering Society Annual Meeting and is part of a National Institutes of Health-funded multi-year study that aims to enhance the consultation process for women undergoing breast reconstruction surgery.
The team conducted a small survey of women who had recently undergone ラーメンベット 評判 reconstruction surgery, asking about their experiences, with particular emphasis on the decision-making process and communication from doctors. Of the respondents, 93% said they would like to have been shown more visual examples of outcomes from different surgical procedures before making a final decision.
“Doctors are conscious of providing too much detail on the worst possible post-surgery outcomes, especially if they are statistically unlikely,” Markey said. “ラーメンベット 評判 concern is that it only serves to cause undue stress on women already under severe pressure.”
But the study found that patients want as much information as possible before making a decision. Without it, many resort to conducting their own online ラーメンベット 評判, which can lead them to viewing post-surgery images that may be unreliable and unverifiable and so increase their stress and uncertainty.
Markey is looking at the broader psychosocial factors at play for women who must choose between different ラーメンベット 評判 reconstruction surgery options, a decision that women currently must make without much context to help inform their choice. This study will help Markey and her team design a patient-specific decision-support system providing personalized visual information about post-surgery outcomes.
Breast ラーメンベット 評判 Research in the ラーメンベット 禁止ゲーム
Reprogramming ラーメンベット 評判 Cells and Creating a Backbone for Personalized Medicine
While mammography is great at detecting certain lesions, only a small fraction of these abnormalities develop into breast ラーメンベット 評判. At this time, there are no good biomarkers that predict which lesions may become life-threatening. Biomedical engineering assistant professor Amy Brock is identifying new, less drastic ways to treat abnormal cells. She’s identifying what triggers the journey to ラーメンベット 評判 in order to develop new interventions that could reverse the growth of malignant tumors early on and eliminate the need for invasive surgery and chemotherapy.
Brock has also developed an innovative barcoding technology to track and tag individual tumor cells. Tagging individual cells will allow Brock and her collaborators at Dell Medical School’s LIVESTRONG ラーメンベット 評判 Institutes to study them in greater depth and treat them with different therapies to learn which ones respond by dying off and which ones come back more resistant.
Stimulating ラーメンベット 評判 with Laser Therapies
Biomedical engineers James Tunnell and Laura Suggs are collaborating to treat breast ラーメンベット 評判 by perturbing immune cells called macrophages to help them find and fight ラーメンベット 評判 cells. Immunotherapy has seen great progress in treating some forms of ラーメンベット 評判, but the response rates in breast ラーメンベット 評判 have been very low. One possible reason is that breast tumors are abundant in a type of macrophage that suppresses the immune response, inhibiting the immune system from recognizing and killing the ラーメンベット 評判 cells. Tunnell and Suggs use low-energy laser light along with specifically shaped nanoparticles to precisely manipulate tumor-associated-macrophage cells, making these immune cells pro-inflammatory and inciting the immune system to attack ラーメンベット 評判. If successful, this strategy will improve immune therapies in tumors that currently don’t respond to treatment.
Using Math to Forecast Breast ラーメンベット 評判 Tumor Growth for Patient-Specific Treatment
Professor Tom Yankeelov develops mathematical models to forecast how ラーメンベット 評判 tumors will grow, change and respond to treatment. Yankeelov and his colleagues in the Center for Computational Oncology, use advanced imaging techniques to measure specific tumor characteristics (e.g. blood flow and proliferation), and then puts these data into biophysical models to predict how a tumor will respond to therapy. Advances in imaging science, applied mathematics and computer simulation make it possible for Yankeelov and his team to build models designed to optimize treatments on an individual patient basis. Importantly, their team is performing these studies in collaboration with US Oncology, Seton Healthcare Family and Austin Radiological Society — a true public-private partnership between biomedical engineers and practicing physicians in the Austin metropolitan area.
“Our goal is to learn the mathematical laws of ラーメンベット 評判, so that ultimately we have a set of equations that we are confident can recapitulate the spatial and temporal development of a tumor,” Yankeelov said.
