Diagno.AI [ Radio.AI | Medi ]

The inspiration for my idea comes while solving two problems:

P-1. There are millions of people in this world without access to proper healthcare and preliminary medical diagnosis.

P-2. Diagnostic error in Radiology is a major cause of patient harm. Even with the tremendous advancements in radiology, an increased understanding of what disease looks like, and greater education of radiology, we still have a persistent high error rate.

And hence to solve these problems was born Diagno.AI

An Artificial Intelligence based Preliminary Diagnosis Platform for patients around the world!

Diagno.AI is an integrated end to end Artificial Intelligence application for the people who instantly need preliminary medical diagnosis and to reduce diagnostic error in Radiological diagnosis by providing fast and accurate results from medical images and reports such as X-Rays, MRIs and CT scans

Diagno.Ai solves the above two problems by providing two modern solutions using Artificial Intelligence and Machine Learning

Automated Preliminary Medical Diagnosis using Medi your personal medical question answering service. It’s basically a doctor in your pocket once you log into the app what it’s gonna let you do is talk to an automated doctor that will give you a medical diagnosis and a treatment plan automatically. Medi is an on-demand medical diagnostic and treatment plan tool.

Diagnostic error reduction using Radio.AI which gives Accurate radiological reports from medical images such as X-rays , MRIs and CT scans using trained deep learning models

Diagno.Ai will provide these services to its users in its first phase of launch and have plans to solve significant medical problems like early-stage cancer diagnosis using AI and data science.

The plan is to build an app that will use different image processing techniques and state of the art deep learning models for disease prediction from radiological images as Deep learning has been proven to be superior in detecting diseases from X-rays, MRIs and CT scans which could significantly improve the speed and accuracy of diagnosis. and for personal medical question answering service, we will use a Natural Language processing (NLP) model called BioBERT trained on over 700K Q&As from PubMed, HealthTap, and other health-related websites for different NLP tasks.

AI healthcare market is expected to reach $45.2 billion USD by 2026 from the current valuation of $4.9 billion USD.

Built With

• adobe
• python
• tensorflow
• xd