AI-For-Medicine and Coursera-DeepLearning.AI-AI-FOR-MEDICINE-SPECIALIZATION

These are competitors, as both repositories offer independent solutions to the same "AI for Medicine Specialization" assignments on Coursera, requiring users to choose one over the other.

Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 19/25
Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 16/25
Stars: 19
Forks: 19
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 17
Forks: 6
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: GPL-3.0
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About AI-For-Medicine

karnaankit/AI-For-Medicine

This repo contains my assignment solutions of AI for Medicine Specialization on Coursera

This collection of assignments helps medical professionals understand how AI can be applied to common challenges in healthcare. It shows how AI models can process medical images like X-rays and MRIs for diagnosis, analyze patient data for disease prognosis, and assist in understanding treatment effects. This is for healthcare practitioners, medical researchers, and clinical professionals interested in leveraging artificial intelligence in their work.

medical-diagnosis disease-prognosis treatment-analysis medical-imaging clinical-decision-support

About Coursera-DeepLearning.AI-AI-FOR-MEDICINE-SPECIALIZATION

shantanu1109/Coursera-DeepLearning.AI-AI-FOR-MEDICINE-SPECIALIZATION

This Repository Contains Solution to the Assignments of the AI for Medicine Specialization from Deeplearning.ai on Coursera Taught by Pranav Rajpurkar, Bora Uyumazturk, Amirhossein Kiani, Eddy Shyu

This project contains solutions for assignments in the AI for Medicine Specialization, helping you learn to apply machine learning to healthcare challenges. You'll work with medical images like X-rays and MRIs to diagnose diseases and segment tumors, and use patient trial data to predict survival rates and recommend treatments. It's designed for medical professionals, researchers, or data scientists looking to integrate AI into clinical practice.

medical imaging disease diagnosis patient prognosis treatment recommendation medical NLP

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