Regular applications are NOW OPEN until May 14th! Apply now @ https://biohackucr.com/ !! BioHack 2021 is open to undergraduates from ALL schools and majors. It is an extremely beginner-friendly hackathon that is health and medicine themed; we hope to see you there! #applicationsopen #application #open #comingsoon #Biohack2021 #hackathon #healthcare #healthcarehackathon #medicine #biology #bio #innovation #compsci #computerscience #hacking #STEM #engineering #science #technology #tech #biotech #biohack #2021
关于我们
This year, the Biomedical Engineering Society returns with BearHack, the annual student-run 24-hour health and medicine-themed hack-a-thon at the University of California, Riverside! This FREE technology competition is all-inclusive, i.e. all three meals (breakfast, lunch, dinner), snacks, parking, merch, and more! Our mission is to foster connections among students and sponsors through the bridging of medicine and technology. We encourage science, engineering, business, and social science students, especially females and minorities, to develop valuable technical and teamwork skills in a safe and encouraging environment.
- 网站
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https://bearhack2024.vercel.app/
BearHack的外部链接
- 所属行业
- 生物技术
- 规模
- 11-50 人
- 总部
- Riverside,California
- 类型
- 非营利机构
- 创立
- 2018
地点
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主要
900 University Drive
US,California,Riverside,92507
BearHack员工
动态
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BearHack转发了
We loved your project!! Your team had a great idea and product!
This past weekend, I had the opportunity to participate in BearHack 2024 with my roommates Osvaldo Ortiz, Omar Nosseir and Jacob Hensley. A few days before the hackathon, we sat down and brainstormed ideas while exploring the possible tracks: Best Beginner, Best UI/UX, Best Wearable, and Best Start-Up Idea. We generated numerous ideas for each track and then realized, why not compete in all? We pooled our creativity and conceived SkinVue! SkinVue is a wearable device and platform designed to scan skin lesions and classify them as benign or malignant. In cases of malignancy, it generates a distribution indicating the likelihood of specific diseases or cancers. Our wearable device ensures consistently high-quality images, which are transmitted to our server housing a convolutional neural network for classification. Following classification, the image and its categorization are stored in the user's account for historical reference and future tracking. For the tech enthusiasts, I leveraged my favorite frontend tech stack, comprising of React, TailwindCSS, Framer Motion, and Redux. Additionally, I opted for an AWS EC2 instance to host our Flask server, housing our CNN model developed and trained using Python and Tensorflow. For our datastore, a PostgresSQL database called Supabase was chosen. Jacob and Osvaldo worked with the Arduino Uno R3 and ArduCam Mini for our hardware setup. Omar crafted the 3D model using Fusion 360 and coordinated its printing with our off-campus 3D printing expert. Jacob and Omar came to a victory at about 2 am fixing an incompatibility with the hardware components giving us the final piece of hope we were looking for. Our diverse skill sets converged seamlessly, enabling us to execute every component—from frontend and backend development to AI modeling, 3D printing, and hardware integration—within 24 hours. Despite the sleepless marathon, we knew it was a venture worth undertaking. We started at 10 am and finished at about 9 am the next day. Within hours, we would come to find out our project had won the Best Overall Hack award! Check out the Github repo here: https://lnkd.in/gYrnD5DK
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We loved your project!! Your team had a great idea and product!
This past weekend, I had the opportunity to participate in BearHack 2024 with my roommates Osvaldo Ortiz, Omar Nosseir and Jacob Hensley. A few days before the hackathon, we sat down and brainstormed ideas while exploring the possible tracks: Best Beginner, Best UI/UX, Best Wearable, and Best Start-Up Idea. We generated numerous ideas for each track and then realized, why not compete in all? We pooled our creativity and conceived SkinVue! SkinVue is a wearable device and platform designed to scan skin lesions and classify them as benign or malignant. In cases of malignancy, it generates a distribution indicating the likelihood of specific diseases or cancers. Our wearable device ensures consistently high-quality images, which are transmitted to our server housing a convolutional neural network for classification. Following classification, the image and its categorization are stored in the user's account for historical reference and future tracking. For the tech enthusiasts, I leveraged my favorite frontend tech stack, comprising of React, TailwindCSS, Framer Motion, and Redux. Additionally, I opted for an AWS EC2 instance to host our Flask server, housing our CNN model developed and trained using Python and Tensorflow. For our datastore, a PostgresSQL database called Supabase was chosen. Jacob and Osvaldo worked with the Arduino Uno R3 and ArduCam Mini for our hardware setup. Omar crafted the 3D model using Fusion 360 and coordinated its printing with our off-campus 3D printing expert. Jacob and Omar came to a victory at about 2 am fixing an incompatibility with the hardware components giving us the final piece of hope we were looking for. Our diverse skill sets converged seamlessly, enabling us to execute every component—from frontend and backend development to AI modeling, 3D printing, and hardware integration—within 24 hours. Despite the sleepless marathon, we knew it was a venture worth undertaking. We started at 10 am and finished at about 9 am the next day. Within hours, we would come to find out our project had won the Best Overall Hack award! Check out the Github repo here: https://lnkd.in/gYrnD5DK
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