Machine Learning in Health Science

📢 We launched the MLHS Apps Hub!

🌍 We invite clinicians, researchers, and everyone interested in digital health to explore MLHS apps. This is a growing hub of real-world, ready-to-use medical, research, and education utilities — running entirely in your web browser, all in one place.

💡 For developers:

• ✅ MLHS is currently seeing ~500 daily unique visitors worldwide (recent trend).
• ✅ Want visibility for your web-based healthcare or research tool? Submit an App Note via your MLHS apps account and get it published and listed.

Start exploring and building now

Synthetica is live!

📢Announcement! ML in Health Science’s new app for medical image augmentation + dataset cleanup.

Synthetica generates realistic acquisition-level variants (findings preserved) and reduces common overlays (text/UI/borders).

Supports:
☢︎ Radiology (XR, DSA/Angio, MRI, Ultrasound, CT*)
🔬 Microscopy (histology / pathology / microbiology)
📷 Macroscopy (endoscopy / dermatology / clinical images)

🔮 Errors in RAG and Agentic AI

New paper in our journal.
Architecture and Workload as Primary Sources of Error in RAG and Agentic AI Systems presents insights gained from over two years of ☸️SAIMSARA development.

The article summarizes practical lessons learned while building a multilayer, agent-based evidence extraction system capable of processing millions of scientific papers and thousands of references at scale.

To our knowledge, no stronger system is currently in operation. Readers aware of comparable or more powerful systems are invited to share references or insights in the comments.

☸️SAIMSARA → now as PDF.

📄 Not just URL/TXT anymore: export a clean, paper-style PDF you can read offline, print, and share with colleagues in one click.

🔮Medical & Healthcare AI Assessment

The AI Act still cannot function effectively, because there are no real, practical comparators that can reliably distinguish black-box, low-quality “AI tools” from genuinely validated, transparent, clinically aligned systems. At ML in Health Science, we have been working on this challenge since 2023. Today, we introduce our latest solution — a fast, structured tool for individual assessment of healthcare AI quality and alignment with human-centered and regulatory expectations. The evaluation takes only a few minutes.

☸️ SAIMSARA Just Got More Powerful

• Premium version powered by a more advanced AI agent.

• Bigger batches — process up to 150 abstracts at once
• Deeper synthesis — expanded token budget (~65k)
• Wider coverage — access to ~50 million biomedical records

⚡ Result: 1000× faster than a human analyst.

⏱️ Stop wasting time searching for biomedical evidence.
☸️ Subscribe to SAIMSARA and take your research to the next level — faster, smarter, and backed by reliable data.

📢 Join the MLHS Editorial Team!

🌍 We invite clinicians, researchers, and digital health experts to contribute as editors and reviewers of innovative digital health project

💡 What we offer:

• ✅ As an honorarium, editors receive 80% of the fees collected for a review they complete. This can be up to $400 USD.
• ✅ Free access to our scientific tools for research, including the ☸️SAIMSARA agent for AI-powered search in biomedical archives and Science 3.0 for blockchain preservation of important research data.

Apply now

🔮Image Preprocessing

Medical images are machine outputs, not holiday photos. In MLHS, every image goes through the same 224×224 bilinear resize (no cropping) at both training and prediction. Augmentations are train-only and used thoughtfully to preserve anatomical truth. Join the discussion on X to learn more!

📢 Digital Health Project 360

💡Digital Health Developers: Limited Clinical Background?

🎯 Until 01.01.26 — Apply for an Editorial Peer Review (FREE, limited to 3 projects!)

• ✅ Clinician-led review & adaptation for real-world medical scenarios
• ✅ Publication with DOI & indexing in leading scientific repositories
• ✅ Blockchain-backed certificate ensuring editorial validation & transparency

🦾Your Bionic Hand

Your Bionic Hand is a Web AI application that allows users to train and calibrate our custom ESP32- and proximity sensor–driven bionic prosthesis without relying on external services. Its low-cost, low-power design makes it accessible to over 95 % (≈3 million) of upper-limb amputees worldwide. For more information, watch the attached video.

🦾Bionic Hand Control with Real-Time B-Mode Ultrasound Web AI Vision

This Web AI application is trained on grayscale 2D ultrasound scans of the forearm, each corresponding to one of four distinct hand positions: Thumb, Forefinger, Open Palm, and Fist. Clicking a photo loads the related ultrasound scan, and the AI model instantly predicts the virtual bionic hand’s movement in real time.

✨Video Classifier

Build custom Web AI models using live video or camera input for real-time computer vision computer vision utilizing transfer learning with the MobileNetV2 layer model and the TensorFlow.js library. The model can be stored after training for deployment, sharing, and retraining with new data. All calculations are performed on the client side and are not transferred elsewhere, ensuring data privacy and safety.

☸️SAIMSARA

Systematic, AI-powered, Medical Scientific Article Review Agent

🔹 Take your first step toward crafting evidence-based meta-analyses, systematic reviews, and new research directions in health sciences.

🔹 Let AI filter and extract relevant research based on your input, providing new directions to build upon.

💰Your MLHS Wallet

DApp designed for easy participation in MLHS ecosystem.

🔹 BNB Network ensures fast transactions

🔹 Reown AppKit enables smooth wallet connection

🔹 1inch Aggregator provides fair and optimized fees

✨Varicose Veins AI Consultant

Hybrid AI built on a Tensorflow.js and empowered by Gemini and Deepseek. 🔍 What does it do?

🔹 Individual risk estimation for developing varicose veins

🔹 Supports patients and healthcare professionals with the latest scientific knowledge on diagnosis, treatment, and prevention of the disease

🔗Science 3.0

Science 3.0 is a DApp and the utility token of the Web3 Journal: ML in Health Science, designed to preserve published articles and valuable health science research data on the opBNB blockchain using the SCI3 Token . 🔑 Use your author or reviewer login credentials for the 📔Web3 Journal: ML in Health Science to access the system for free.

📊Editorial Poll

This web application is a poll associated with the corresponding editorial, "Artificial Intelligence in Academic Writing: Time for Science 3.0," published in Web3: Journal of ML in Health Science. Participate in the poll and share your thoughts in the article's comments section.

🔮Image Patching & Segmentation

Computer vision utilizes numerical color values in the RGB scale for image preprocessing, resulting in 255 x 255 x 255 possible color variants for each pixel. This complexity can make the analysis of high-resolution images challenging. Dividing images into smaller patches helps balance computational resources. This tool demonstrates how visual content is transformed into numerical values for each patch and the entire image.

🔮AI Markov Chain Text Generator

This experimental tool uses Markov Chains and TensorFlow.js Universal Sentence Encoder to generate new text on the client side based on input information, without relying on large language models.

✨Limb Salvage Prediction

The computer vision model provides the ability to predict the probability of lower limb salvage or loss in peripheral artery disease patients using pedal angiograms (DSA) in sagittal view.

✨PROOF Transformer Chat

Open-source AI chat powered by the Gemma2b. It runs on your device, ensuring full privacy - crucial in healthcare settings!

🔹 Tasks: Text generation, context extraction, and conversation, including chat with PDF documents.

⚠️CAVE: Mobile devices are currently not supported! During the first start, Gemma2b will be loaded, please be patient. Subsequent starts will be much faster.

✨AI Snake

Learn the principles of machine learning through gameplay. The Snake is guided by a reinforcement learning using neural network predictions, with training data generated from auto gameplay. Experiment with parameters and observe the performance. If you would like to see how the ML works, right-click, select "Inspect," open the Console of your desktop browser, and enjoy the heartbeat of the machine.

✨List of WebAI applications

🗃️️️ In the list of deployed WebAI applications you can find model trained and deployed in the Web AI Playground. Each model has an individual link to use and share. This list is moderated. If you find an invalid model, please contact us.

✨Web AI Deployer

Create your own web applications using the AI model trained in the Playground. Simply upload the model, add a cover image, and press the "Submit" button. After submission, you can add a description, your custom data, and your Web3 wallet if you wish to receive donations and monetize your work.

✨Audio Classifier

Beta-Test. Control the position of the circle indicator with your voice.

✨Data Classifier

Build custom machine learning regression and classification web applications from numerical data using feedforward neural networks powered by TensorFlow.js. After training, the model can be saved for deployment, sharing, or retraining with new data. All computations are performed locally on the user’s device, ensuring full data privacy and security.

✨Image Classifier

Build custom computer vision web applications from images utilizing transfer learning with the MobileNetV2 layer model and the TensorFlow.js library. The model can be stored after training for deployment, sharing, and retraining with new data. All calculations are performed on the user side and are not transferred elsewhere, ensuring data privacy and safety.

🔮World Map Overlay: Cancer Incidence and Earth Emissivity

This web app overlays GLOBOCAN cancer incidence data with NASA's Earth emissivity maps to explore the potential association between chronic infrared exposure from Earth's emissivity and overall cancer incidence rates. For more information, please refer to the accompanying article.

✨Smartphone Camera for Angiographic Computer Vision

This Web AI app is a computer vision tool for classifying femoropopliteal angiograms based on the FP GLASS classification, as detailed in the accompanying article. For comprehensive guidance, please refer to the research article.

𝚿 Xavatar

Opinion Piece published in our Journal on the human-centered “Xavatar” project, which aims to offer unique and engaging experiences by creating a deeper sense of presence and interaction for patients with mobility disorders. Read the paper, try the editorial application "Immersive Content", and share your comments on the use of extended reality (XR) in medical education.

𝚿 AI_4_Healthcare

Opinion Piece published in our Journal on the human-centered “AI_4_Healthcare” project, which explores proven approaches to utilizing AI in healthcare. Read the paper, try the editorial application "Keyword Generator", and share your thoughts on using proper search strategies and systematic literature reviews to achieve accurate and reliable information extraction in healthcare.

📊Research Poll

This web application is a poll associated with the corresponding article, "Confounders in Predictive Medical Models: The Role of Religion," published in Web3 Journal: of ML in Health Science. Participate in the poll and share your thoughts in the article's comments section.

📊Research Poll

This web application is a poll associated with the corresponding article, "Confounders in Predictive Medical Models: Roles of Nationality and Immigrant Status," published in Web3 Journal: of ML in Health Science. Participate in the poll and share your thoughts in the article's comments section.

🔮CME Complexity Score: Resistance to AI Agents

This web app calculates the complexity score of CME online courses to evaluate their resistance to AI agents. For more detailed information, please refer to the accompanying article.

📊Research Poll

This web application is a poll associated with the corresponding article, "Do You Consent to the Use of Your Biological Data for Training ML and AI Models? Online Survey Targeting Clinicians and Researchers" published in Web3 Journal: of ML in Health Science. Participate in the poll and share your thoughts in the article's comments section.

📊Research Poll

This web application is a poll associated with the corresponding article, "Do You Agree with AI Making Decisions About Your Treatment? A Comparative Survey of IT and Healthcare Practitioners," published in Web3 Journal: of ML in Health Science. Participate in the poll and share your thoughts in the article's comments section.

📢 ML in Health Science is live!

💡 On December 30, 2023, we launched the ML in Health Science: 🔗 Blockchain verification.

Our mission is to bring clinicians and digital health developers into one community and to support human-centered, patient-oriented science in the age of AI and machine learning.

📖 Why ML in Health Science — the philosophical introduction and first publication in our journal:
https://doi.org/10.62487/e4ccm968

✍️ Write the new chapter of health science with us!