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Healthcare

AI Enabled Cervical Cancer Screening

A research team led by investigators from the National Institutes of Health and Global Good has developed a computer algorithm that can analyse digital images of a woman’s cervix and accurately identify pre-cancerous changes that require medical attention. This AI approach, called automated visual evaluation, has the potential to revolutionize cervical cancer screening, particularly in low-resource settings. To develop the method, researchers used comprehensive datasets to train a deep, or machine, learning algorithm to recognize patterns in complex visual inputs, such as medical images. The approach was created collaboratively by investigators at the National Cancer Institute and Global Good, a fund at Intellectual Ventures, and the findings were confirmed independently by experts at the National Library of Medicine. Read More

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Insurance

AI Estimates Vehicle Repair Cost After Accident

The Korea Insurance Development Institute is developing an AI-based assessment tool dubbed Automobile repair cost On-line Service-α (AOS-α). The system’s AI will estimate vehicle repair costs by analysing pictures of car wrecks caused by traffic accidents. It will also recognize which parts of the car were damaged and the degree of damage. Additionally, AOS-α will speed up the insurance claim process by automatically identifying a vehicle’s license plate and then retrieving insurance contract information. When the institute did a test run in September 2018, the AI was 99% accurate at recognizing different car parts, and 81% accurate at recognizing the degree of damage. The institute is planning to invest approximately $3.56 million in the project and AOS-α is expected to launch as early as the second half of this year. Read More

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Sports

AI Can Predict Your Tennis Opponent’s Next Shot

Correctly predicting your opponent’s next shot can be the difference between winning and losing in tennis. Now, researchers from the Queensland University of Technology (QUT) have created an AI that can analyze a specific player’s shot decisions to predict what they’re likely to do next — and it could change the sport for both players and fans. In a paper published, QUT researchers, describe how they created their seemingly psychic tennis AI by combining the mental processes human players use to predict shots with a neural network. The QUT researchers used data on 8,780 shots taken by tennis pros Rafael Nadal, Roger Federer, and Novak Djokovic at the 2012 Australian Open Men’s singles to train, test, and validate their tennis AI. The Hawk-Eye ball tracking system recorded the data, and it included everything from the ball’s trajectory, speed, and angle to the player’s foot movements. After training the system using about 70% of the available data, the team used about 25% of it to test the AI’s ability to predict the next shot’s type (winner, error, or return) as well as its location. It was able to predict the type of shot with an accuracy between 82.65% and 89.01% and the location within 0.93 meters on average. Read More

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Healthcare

Novel AI Tool Can Predict How Flu Spreads

Scientists have used AI to create a tool that can track the spread of influenza and predict where the highly contagious infection may travel. The approach, called ARGONet, makes more accurate predictions than the earlier high-performing forecasting approach, ARGO. The ARGONet approach uses machine learning and two robust flu detection models. The first model, ARGO (AutoRegression with General Online Information), leverages information from electronic health records, flu-related Google searches and historical flu activity in a given location. To improve accuracy, ARGONet adds a second model, which draws on spatial-temporal patterns of flu spread in neighboring areas. The machine learning system was trained by feeding it flu predictions from both models as well as actual flu data, helping to reduce errors in the predictions. The system continuously evaluates the predictive power of each independent method and recalibrates how this information should be used to produce improved flu estimates. Read More

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Customer Service

New AI Platform Will Help Businesses Improve Customer Interactions

Verizon has launched a world-class suite of solutions that blends human and artificial intelligence to enhance the customer engagement experience. Digital Customer Experience (CX) is an end-to-end managed service that deploys automation into enterprise and business owner’s customer experience tools. Through Digital CX, consumers who contact a business – whether on social media, chat, email, text, or over the phone – will receive personalized experiences based on past interactions that are delivered through a mobile-first interface; allowing customer service representatives to access information seamlessly between platforms 24/7. The solution provides a deliberate method of collecting insights, learning from them, and quickly developing efficiencies. Digital CX is made up of four solutions, namely, Virtual Agent, Live Agent, Knowledge Assist and Social Engagement. The solution is currently available in the US and is slated for international release. Read More

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Defence

AI-controlled Weapons That Don’t Need Human Operators

The US Army is looking into the possibility of having AI control the aiming and firing of some of their weapons systems. The reason, quite simply, is that computers can react faster than people. Bruce Jette, the US Army’s Assistant Secretary for Acquisitions, Logistics and Technology stated that this may be the only way to defeat incoming enemy weaponry. According to Jette, the Army is progressing slowly on its development of AI controlled weapons because of the pressure to have a human in the loop at all times. Read More

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Healthcare

AI App to Tackle Malnutrition

Germany-based non-profit Welthungerhilfe has developed an AI smartphone app, powered by Microsoft Azure, to tackle malnutrition in India. The Child Growth Monitor - a cloud-based app powered by Microsoft Azure and AI services - can detect malnutrition and enable health workers to identify and provide care to children suffering from chronic undernourishment. The app will help health workers scan 10,000 children under the age of five for signs of malnutrition, across Maharashtra, Madhya Pradesh and Rajasthan. The app uses an infrared sensor available in some smartphones to capture 3D measurements of a child's height, body volume and weight ratio, as well as head and upper arm circumferences down to the millimetre. The app loads that captured data into Microsoft Azure. Nutritionists and IT specialists then evaluate the scans by using Microsoft AI solutions, pinpointing a child's dietary health. The new app will hugely impact the early identification of children suffering from malnutrition, thereby reducing the treatment time. Read More

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Miscellaneous

AI to Decode the Ultrasonic Language of Rodents

A new type of AI called DeepSqueak can decode mouse speak and help researchers match the vocalizations with behaviors. Scientists at the University of Washington came up with the software, which analyzes high-pitched, or ultrasonic, mouse vocalizations and turns them into sonograms, or visual representations of the sound. Machine-learning algorithms then analyze those sonograms for patterns that can relate to behavior and emotion. The aim of the mouse-translator isn’t just to understand what they are saying to each other. The lab studies the psychological aspect of drug addiction, and knowing which calls indicated positive and negative emotions can help the researchers understand what the animals are experiencing during experiments. The team also realizes that listening in on lab rodents could be useful for other researchers or in order to improve the well-being of the animals. Read More

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