PyTorch implementation of Grouped SSD (GSSD) and GSSD++ for focal liver lesion detection from multi-phase CT images (MICCAI 2018, IEEE TETCI 2021)
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Updated
May 11, 2022 - Python
PyTorch implementation of Grouped SSD (GSSD) and GSSD++ for focal liver lesion detection from multi-phase CT images (MICCAI 2018, IEEE TETCI 2021)
MediScan: AI-powered bone fracture detection system achieving 99.8% accuracy through deep learning. Features real-time X-ray analysis, transparent Grad-CAM visualizations, and clinical integration tools. Built with Python/FastAPI backend and responsive HTML/CSS frontend, making advanced medical diagnostics more accessible to healthcare providers.
Sparrow AI - API for disease diagnostics
Flask based web app with five machine learning models on the 10 most common disease prediction, covid19 prediction, breast cancer, chronic kidney disease and heart disease predictions with their symptoms as inputs or medical report (pdf format) as input.
Medical Diagnostic Module Programmed with Python and using Fuzzy Logic
A medical diagnosis system
Medical Diagnosis system using Prolog
Machine learning models for detection of diseases.
Quick Android app for medical diagnosis, currently just using Endless Medical API
Machine learning model in Julia classifies patients with Diabetes Mellitus, Diabetic Retinopathy, and Diabetic Nephropathy using biomarkers Hornerin and SFN, plus clinical features like age and diabetic duration, for diagnostic applications.
Egészségügyi szűrőprogramok, orvosi tesztek eredményességének vizsgálata.
AI-driven disease prediction model based on symptoms using machine learning.
ML for early diagnosis of Alzheimer's disease. Results and jupyter notebook published on GitHub pages.
ML for stroke prediction, Intelligent Systems course (3rd year, 2nd semester)
An AI-powered medical assistant that uses machine learning and deep learning to classify diabetes, detect pneumonia and diabetic retinopathy from images, and provides intelligent health consultation via a Gemini 2.5 Flash chatbot.
This repository features cutting-edge machine learning applications in healthcare, addressing diverse challenges such as dermatological lesion detection, ECG signal categorization, gland segmentation in colorectal cancer, pathological myopia prediction, and pneumothorax identification.
ML for MRI image classification, Intelligent Systems course (3rd year, 2nd semester)
CancerGuardian is a machine learning-powered web app that helps predict breast cancer diagnoses based on cytology measurements. 🩺✨ Built with Streamlit, Scikit-Learn, and Plotly, this tool visualizes tumor characteristics and provides predictions using a trained model. 🚀
AI-driven heart disease prediction model using machine learning for early diagnosis.
A deep learning model built with TensorFlow for the rapid, non-invasive classification of Type 2 Diabetes using Raman spectroscopy data. Achieves 93.75% accuracy with 100% recall for diabetic cases.
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