ML in Health Science
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Medical Publisher and Journal for Web-Based ML Applications in Healthcare and Research (ISSN 2942-8726)
$MLHS
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Indeed, code is also the future of healthcare research — write it with us in our Web3 journal. ✍️🖥️ #FutureOfHealthcare #Web3Research $MLHS
ML in Health Science pinned «In our AI playground, you can build and explore common AI models without any coding. Try it out and get inspired to deploy your own healthcare AI solutions. We offer assistance with development and promotion. https://mlhs.ink/Playground/»
We are proud to announce the deployment of our next peer-reviewed medical #WebAI model! This #ComputerVision tool predicts outcomes in peripheral artery disease using angiograms. #HealthcareAI #DeSci

Test the model live here:

https://mlhs.ink/amputate/
🎉 Exciting News! 🎉

We are very proud that our latest healthcare #WebAI model has been recognized and featured in the latest issue of the Web AI Monthly Newsletter by Jason Mayes and #Google .

This milestone underscores our commitment to leveraging client side AI technology to advance medical research and patient care.

Join us to ✍️ write and 🖥️ develop the next chapter of medical research together!

#AI #WebAI #HealthcareInnovation #MedicalResearch #TechnologyForGood

https://www.linkedin.com/newsletters/web-ai-monthly-6895540524061736960
💡Exciting Announcement!

We are proud to introduce our next healthcare #WebAI application: Varicose Veins AI Consultant! 🩺

🧠 This custom hybrid AI is powered by a #Tensorflow.js neural network, enhanced with #Gemini Flash and #Deepseek.

🔍 What does it do?
✅ Provides individual risk estimation for developing varicose veins over a lifetime 🏥
✅ Delivers up-to-date insights on diagnosis, treatment, and prevention of the disease 📊💊
✅ Supports patients and healthcare professionals with the latest scientific knowledge 🔬📚

🌐 Try it out now! 👉

#AI #HealthTech #MedTech #MachineLearning #VaricoseVeins #MedicalAI


https://mlhs.ink/varicose/
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📌Announcement!

☸️SAIMSARA – the Systematic AI-powered Medical Scientific Article Review Assistant.☸️

Your first step toward crafting evidence-based meta-analyses and systematic reviews in health sciences.
Let AI filter and extract research based on your input, generating new directions to build upon.

#PubMed #NCBI #PROSPERO #NIHR #PRISMA

https://mlhs.ink/saimsara/
Most #ML and #AI solutions are developed for general purposes. Therefore, #MLHS would like to share insights from the recent #WebAISummit highlighting our top four tools with potential applications in #MedicalResearch:​

🔹Client-Side #DepthEstimation: this tool warrants research to enhance interpretation in 2D #Medicalimaging. Example of such conversion in the attached medical image

🔹Optimizing Web AI Performance with Chrome's Built-In APIs: this advancement translates to more efficient and responsive tools for research.​

🔹Applying #BodyPoseEstimation for #Physiotherapy: this approach warrants head-to-head comparisons and further research.​

🔹#SimpleML for #GoogleSheets: this add-on enables to perform #MLprediction tasks without extensive coding knowledge.​

Many thanks to the #WebAI community for their valuable contributions to future-specific research.

Access the entire session here: https://www.youtube.com/playlist?list=PLNYkxOF6rcIAEVKJ98bDkQRkwvO4grhnt
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🚀 Announcement: Introducing our latest MLHS Playground extension—Video Classifier!

This application enables you to easily create custom #WebAI models directly from live videos, including camera feeds or connected video capture devices. Just follow the simple, step-by-step instructions and start building privacy-safe #medicalAI models!

https://mlhs.ink/Playground/#SVC
🦾 Lost limbs can’t be fully restored — but bionics can bring motion back, on demand.

Bionic systems translate anatomical sensor data into precise movements. The more accurate the anatomical input, and the simpler its transformation into prosthetic motion, the closer we get to natural, intuitive control.

💡 B-mode ultrasound offers real-time, high-resolution imaging of muscle activity. But its interpretation is complex, and the anatomical variance between users makes it computationally expensive.

⚡️ Enter #WebAI — enabling real-time client-side processing and training, right in the browser. With it, users can train and retrain their bionic limb model independently, without external services or data transfers.

🚀 Check out the latest research from our journal showcasing Web AI–powered ultrasound control of a virtual bionic hand.

https://youtu.be/D-MYmzrhI7w

Research paper: https://doi.org/10.62487/vjzf7254

#bionics, #ultrasound, #prosthetics , #healthcareai , #medicalai
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Introducing latest #MLHS prototype: a #WebAI-controlled in the browser #bionichand, built on the #ESP32 and #proximity sensing, fully adaptable to muscle contractions.

More updates, presale, technical breakdowns coming soon.

Follow for the future of bionics for everyone!
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🧠 One Year Later — This VR Alzheimer’s Project Is Thriving
Exactly one year ago, ML in Health Science published an article on a visionary project led by Jason P. Rothberg and developed by Aboot Studios (Xavatar) — a virtual reality simulation placing users inside the mind of a person with Alzheimer’s disease.

We are pleased to see how this project continues to evolve and gain traction. Its unique approach, combining immersive VR with clinical insights offers medical students an unparalleled educational experience that fosters deep empathy and understanding of cognitive disorders.

A year has passed — the project is alive, growing, and more relevant than ever.


🔗 https://www.kite-uhn.com/news/kite-creates-cohort


#Alzheimers #VRinMedicine #MedicalEducation #DeSci #MLinHealthScience #Geriatrics #Neurodegeneration #DigitalHealth #Xavatar #AbootStudios
💡 Digital Health Developers: Limited Clinical Background?
Until 01.01.26 — 3 FREE Editorial Peer Review!
✅ Clinician review & adaptation for real medical scenarios
✅ Publication + DOI + scientific repository
✅ Blockchain-backed certificate
🔗 mlhs.ink/Certificate
#DigitalHealth #MedTech #HealthApp #AIinHealthcare
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🎓Medical images are machine outputs, not holiday photos.
In our computer vision pipelines, we standardize to 224×224 bilinear—no crop—at both train & predict.
mlhs.ink/Playground/#SIC mlhs.ink/Playground/#SVC
Identical steps, no drift, reproducible results. #MedAI #DigitalHealth
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ML in Health Science pinned «💡 Digital Health Developers: Limited Clinical Background? Until 01.01.26 — 3 FREE Editorial Peer Review! ✅ Clinician review & adaptation for real medical scenarios ✅ Publication + DOI + scientific repository ✅ Blockchain-backed certificate 🔗 mlhs.ink/Certificate…»