CasPrep’s Post

I've been playing with a brain tumor MRI dataset working to get deep learning working on it to see if it could diagnose brain tumors. After a couple weeks I got it working! I've attached all the code here with an explanation on how it works: https://lnkd.in/e3BsryWx Currently the model is performing at 68%... random chance would be 25% at best based on the dataset which can be found here: https://lnkd.in/en3DvqJh Currently it looks for No Tumor, Meningioma, Pituitary and Glioma. Next step, moving it to Amazon Sagemaker so I can get it some real horsepower for training. Also, there are a lot of pre-built models that already perform this task pretty well supposedly, at least papers show ResNet doing it quite well. This was more for learning how CNNs work, building something from scratch and then improving it through tuning than anything else.

Exploring the Medical Robots Market: Size, Growth Drivers, and Future Prospects Market Growth Drivers 1. Reducing Medication Errors: Automated pharmacy systems significantly reduce medication and dispensing errors, prompting governments to encourage their adoption. 2. Surgical Advancements: Growing use of robotic-assisted surgeries in various procedures offers improved precision and recovery times. 3. Emerging Economies: Rising healthcare expenditure and medical tourism in countries like Brazil, Russia, India, China, and South Africa provide lucrative opportunities. Challenges 1. High Costs: Robotic-assisted surgeries and systems like the da Vinci platform entail significant costs, hindering widespread adoption. 2. Regulatory Environment: Stringent regulations in developed countries can delay market entry and innovation. Future Prospects Emerging economies are set to be key growth areas for medical robotics, offering lower-cost treatments and more flexible regulatory environments. The increasing trend in healthcare expenditure and surgical procedures in these regions is expected to drive substantial market expansion. Key Players in the Market Prominent players in the medical robots market include: Intuitive Stryker (US) Medtronic (US) BD(US) Omnicell (US) ARxIUM (Canada) Asensus Surgical(US) ZAP Surgical Systems, Inc.(US) Renishaw (UK) Smith+Nephew (UK) Zimmer Biomet (US) Damalie Innovation Holdings Group (DIH Group) (US) Accuray (US) CMR Surgical (UK) Ekso Bionics (US) BIONIK Inc. (US) Lifeward. (Israel) CYBERDYNE INC.(Japan) avateramedical Digital Solutions GmbH (Germany) Johnson & Johnson (US) Swisslog Healthcare (Switzerland) Relay Robotics (US) #Aethon (US) Xenex (US) ZOLL Medical Corporation (US) The medical robots market is on a dynamic growth trajectory, driven by technological advancements, increasing healthcare demands, and emerging market opportunities. Stakeholders and investors can leverage this comprehensive report to navigate the market landscape and capitalize on future growth prospects. 🔗 https://lnkd.in/diAQDk3d 🔗 #MedicalRobots #HealthcareInnovation #RoboticSurgery #PharmacyAutomation #MarketResearch #HealthcareTechnology #FutureOfMedicine #GlobalHealthcare #InvestmentOpportunity #EmergingMarkets

Data Analytics Project Series: Predicting Blood Donations Blood transfusion saves lives – from replacing lost blood during major surgery or a serious injury to treating various illnesses and blood disorders. Ensuring that there’s enough blood in supply whenever needed is a serious challenge for health professionals. According to WebMD, “about 5 million Americans need a blood transfusion every year”. Our dataset is from a mobile blood donation vehicle in Taiwan. The Blood Transfusion Service Center drives to different universities and collects blood as part of a blood drive. We want to predict whether or not a donor will give blood the next time the vehicle comes to campus. Credits to DataCamp Project: https://lnkd.in/eafFVZaE Healthcare Projects: https://lnkd.in/e8mXp4Tj #Dataanalytics #machinelearning #Datascience #healthcare

The EasyShift and EasyBoost systems from Seneca Devices are designed to allow one nurse to move a patient. These products can be used with any standard or bariatric hospital bed mattress. This innovative technology was the #1 request from the nurses at Duke Health. Please see the information below for more details. Any referrals to the Safe Patient Handling directors at hospitals or rehab centers in Wisconsin or across the U.S. are appreciated. #asphp #ana #medicaltechnology How EasyShift was Created EasyShift was designed and developed by clinicians and engineers through the Duke School of Nursing Health Innovation Lab to create a solution for patient repositioning that is high tech and low touch. The clinical team said that pulling patients up in bed is a daily task that is both time-consuming and physically strenuous. It often takes 10-20 minutes to gather enough staff together in the room, and boosting is a primary cause of repetitive musculoskeletal strain for caregivers. After early prototypes were designed by the Seneca team and tested at the Health Innovation Lab, clinicians suggested the device should also turn the patient side to side, since this is often done while the team is assembled. Enabling just one caregiver to both turn and boost the patient would promote frequent repositioning, as well as streamline workflow for sheet change, skin care, peri care, placing mobility aids, and more. This would save time for front-line staff and eliminate two of the leading causes of caregiver musculoskeletal strain. To make this workflow possible, the Seneca team designed a mattress overlay with inflatable cushions that can gently shift the patient up in bed and also turn side to side. The cushions are inflated by an air pump unit that hangs on the foot of the bed, which is controlled by a remote that the caregiver can use at the bedside. Special thanks to our key partners at the Duke University School of Nursing Health Innovation Lab. LEARN MORE www.senecadevices.com

Want to join a sports medicine listserv to collaborate, network, find/receive referrals, and consult on complex cases? Want to connect with a medical community that does not have a consistent virtual platform? Join the free ever-improving MSK Experts at https://lnkd.in/gmFjFaPn! This platform is built by the users, moderated by the users, and constantly improving due to user interface, feedback, and suggestions. It is not restricted to just sports medicine and musculoskeletal medicine; you can create your own community such as family medicine, pediatrics, or addiction medicine. It provides an effective and efficient user-friendly platform to index posts, find answers from trusted experts in the field, and provide a library of videos/photos of medical information. Hope to see you/read you on MSK Experts! https://lnkd.in/gcmyuwQG

Ophthopedia Update:Safety and Effectiveness of Smooth Incision Lenticular Keratomileusis (SILKTM) Using the ELITA(TM) Femtosecond Laser System for Correction of Myopic and Astigmatic Refractive Errors [Corrigendum] #Ophthomology #Eye #Ophthotwitter

Introducing Synapse: Your Ultimate Study Companion! Thrilled to announce the beta version of Synapse, the innovative revision website backed by psychological studies, is now available - and it's completely free! Check it out at https://synapse.education. Say goodbye to ineffective study methods! Synapse is meticulously crafted with memory principles in mind. For example, instead of passive rereading, we utilize techniques like active recall, scientifically proven to enhance learning outcomes. Researched as part of my EPQ (Extended Project), Synapse is designed to optimize your revision sessions based on proven psychological principles. Explore Synapse today and elevate your revision experience. Join us in revolutionizing the way students study! #Synapse #RevisionWebsite

🔎 An interesting article published by Bertalan Meskó, MD, PhD https://lnkd.in/dVNhrhB5 "The issue of data annotation is reflected well through a simple example: the challenge of recognising cats in images. Therefore, the way developers have been tackling this is by feeding the algorithm with a lot of images of cats and letting the algorithm find out its own rules for recognizing a cat. This requires not only images of cats but annotated ones where a person has previously marked the area on the image that represents a cat. The same rule applies to data obtained in medicine. Medical images, medical records, photos and other scans all require annotation by a professional to make sure the algorithm learns the right rules and draws useful conclusions " 🚀 In our Venture Studio, we develop a web-based platform for Gastroenterologists - EndologiQ ( https://lnkd.in/dX8tQh98) to help them capture and store annotated images and videos and to write their medical reports in a standardised and qualitative way. We do think that this is the first step in developing a more comprehensive algorithm which will be able to assist doctors in performing the medical procedures. But this is only the beginning, "If data annotation becomes an appreciated, rewarded and respected part of practice, its immediate consequence will be making machine and deep learning algorithms much more precise in radiology, pathology, cardiology, oncology, among others in recognizing patterns, supporting diagnoses, and designing treatment pathways" What do you think about this subject? #healthtech #innovation #AIinmedicine

The amazing Barak Danin is always sharing past lectures from conferences just before the next ones are coming. This is how I got in my mail this absolute gem of a lecture - how to design medical interfaces to add trust by the users. Adi Simon shares amazing examples of how to reorganize the data on your interface to build the trust the medical practitioners need in order to actually utilized the product. Highly recommended to anyone building medical systems. The lecture is free to watch after a quick registration (Unfortunately in Hebrew). #fertility #productmanagement

In our exclusive Q&A, Dassani debunks some myths and misconceptions about adding sleep dentistry to a GP toolbox, shares which steps were most critical for practice growth and stability, lists her favorite clinical technologies and more. https://lnkd.in/gHDFKqxq