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We are leveraging machine learning to facilitate everyday communication of people with hearing disabilities, making the world more accessible and inclusive for them.
Problem:Caring at home is demanding and challenging Solution:Care-centric soft- and hardware leveraging data & AI Impact:Support 40m caregivers worldwide, and improve the quality of care of millions
The AI Risk Inspector is an easy-to-use application to help companies check if their AI use case complies with the EU AI Act and get recommendations to improve trustworthiness of their product.
Around 20% of cocoa yield in Ghana gets lost due to diseases, we provide an application that uses an image detection model offline on mobile phones to predict diseases to mitigate loss, even in fields
AI-based Melanoma Detection in a Snap! Our goal is to build a decision support system to help general practitioners to detect melanoma in its early stage.
We propose a concept including design, model development, and data synthesizing for a disease prediction application.
We help farmers reduce their cost and maximise their harvest by supporting them to make a more informed decision when taking care of their crop.Thereby we reduce food waste and help ending word hunger
Quiz App for Medical students to brush up on their diagnosis skills
AIDAR uses state-of-the-art ML models to analyze all relevant data sources about large disasters to give response personnel the best action recommendations.
Fighting cancer before it can harm you Scan the spot - get results - take action
Diseases and human mistakes cost the average farmer in Ghana huge portions of their potential harvest. Our App will help to identify what plagues the crops and give instructions how to fight it.
An android AI application that detects tomato leaf disease and provides suggestion to minimize the effect of the detected cause. The application has been translated in Twi, a native Ghanaian language
We developed a game training radiologists to find diseases in chest-CT's side-by-side with an AI image classifier.
A smartphone app and trained neural network help doctors in detecting melanomas.
We built an early detection app for respiratory diseases, making it possible to detect them before symptoms show up. This will tremendously help preventing the spread of said diseases.
-Used GPT3 to augment dataset -Identified laws of risk from paper -Use GPT3 to check if a law is violated + which -Use BERT trained on our add. data to determine if human interaction takes place
We present an easy-to-use mobile app for farmers to detect diseases in tomato and cocoa plants. The app also suggests the appropriate remedy so that the farmer can take timely action.
Browser extension in order to protect users from hate speech.
Censor hate-speech directly in your browser through a Google Chrome extensions that categorizes text sentiment.
Model for generating daily alarms of different strength to warn users of possible sickness before symptoms show up, based on heart rate and step count data from wearables.
Data obtained from a smartwatch was analyzed and preprocessed in order to create an augmented dataset to train a model for pre-symptomatic detection of infectious diseases.
Problem: Weeds are an unwanted intruder and steal nutrients, water, land, and other critical resources to grow healthy crops. Computer vision technology can detect the presence of weeds.
Use AI to reduce food prices optimally (for example when it is near to its expiry date). This will potentially and hopefully reduce the amount of food waste, and make groceries more affordable.
Webapp which recognizes tuberculosis, pneumonia, covid and healthy CT chest images to train medical students
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