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Using the retina images of the eye, it can detect the possibility of diabetes in a person with the help of Pytorch
There a lot of time when we are not connected to internet and therefore we can't find the actual path to our destination. But in this project we can find optimized path using AI with previous data
Model based on statistics of each player in the team, such as goals, goals in first period, goals in second period, home games, etc.
An app that gives control of data to the user and gives recommendations and advice.
Get faassst information about the corona outbreak, because who likes to google?
Interpreting Twitter's small talk
Web API/Extension to prevent misinformation and spread of panic caused by corona virus related fake news.
Hand Write Code to the Compile
Most hospitals match patient data manually, and computer programs achieve about 90% accuracy. We have developed a machine learning algorithm to automatically match patients with 95% accuracy.
Detects atopic eczema in babies. Used by 3rd-world midwifery nurses.
We hypothesize that public awareness of disease outbreaks correlates negatively to the number of arrivals from China into the US.
Nopanic.io aims to provide contextual information in order to help contain the COVID19 outbreak. This web app provides guidelines based on the user's location to help them navigate the outbreak.
Vaughn explores the data and discusses ideas for how anomalies can be detected.
Our idea is to use data analytics in order to better process the data, find relationships between channels, and then attempt to reduce the costs of operation after identifying duplicate sensors.
We use Facebook’s Open Source Prophet library to predict future coronavirus cases worldwide based on current trends and present the data to users in a simple, map-based graphical interface.
Explore the data provided by caterpillar and get insights on the data
An efficient and interesting way to visualize and interpret the spread of the COVID-19 epidemic
Our mission is to provide free and accessible healthcare services for everyone through the use of AI image analysis diagnosis, community engagement, and access to educational materials.
Accessing State-of-the-Art Data for VR experiences
Classification by autoregression
Applied SotA Machine Learning to Predict Sale Prices of Houses, given Non-Trivial Features.
NHS challenge. We tried to analyze and predict the efffectiveness and prevalence of nicotine across the UK.
We looked to develop a method to advise potential AirBnB hosts on the right locations and types of properties to invest their time and money into
Here we aim to use NHS data to help better manage resources and predict future disease burdens in the near future using Bayesian RNNs.
