Latest Data Updates: Top News Highlights in Brief
In the realm of technology and healthcare, AI systems are proving to be a valuable asset. Here's a roundup of some recent developments.
Snapchat has ventured into healthcare education with a new augmented reality lens. The AI-powered CPR teaching lens guides users through the steps of cardiopulmonary resuscitation, displaying a virtual human dummy and providing tips on the best speed and frequency of chest compressions.
Meanwhile, researchers at the Graduate School and University Center of the City University of New York have developed an AI system that can predict the efficacy of new drug compounds in humans. This system was tested with approximately 9,800 patients and identified drug combinations that matched existing clinical observations.
IBM and Cleveland Clinic have partnered to deploy the first quantum computer dedicated to healthcare research in the United States. The AI system being used for healthcare research at IBM and Cleveland Clinic will be utilized for biomedical discovery, emerging pathogens preparation, and drug optimization.
In another exciting development, Tasmania's Fire Service and Minderoo Foundation are trialing an AI-powered fire detection system in remote locations during the upcoming bushfire season. The system uses cameras to detect smoke and alerts first responders, and automatic weather stations to collect real-time data during wildfires.
Researchers at Pennsylvania State University have made strides in predicting Autism Spectrum Disorder (ASD) using medical claims data. They have created machine learning models that can predict a child's chance of developing ASD between the ages of 18 months and 30 months old using medical claims data.
AI systems show promising but still developing effectiveness in predicting ASD using medical claims data and related healthcare information. Recent studies apply machine learning and deep learning methods to demographic data, behavioral assessments, and multimodal clinical data for ASD detection. However, the predictive accuracy reported for early ASD classification ranges widely, with some logistic regression models on nonclinical datasets achieving relatively high performance.
While direct evidence on claims-data-only AI models achieving high predictive accuracy for ASD remains limited, the field is advancing with hybrid deep learning models and large-scale datasets. The predictive accuracy improves when claims data are combined with behavioral and neuroimaging information.
In sum, AI systems can effectively support early ASD prediction using complex healthcare data, including claims data, but diagnostic accuracy improves when claims data are combined with behavioral and neuroimaging information. The field is advancing with hybrid deep learning models and large-scale datasets, yet medical claims data alone may yield moderate prediction performance compared to multimodal approaches.
These developments highlight the growing potential of AI in various sectors, from healthcare education to disease prediction and fire detection. As research continues, we can expect to see even more innovative applications of AI in the future.
- The use of AI is not limited to healthcare education and disease prediction; it is also being trialed for fire detection, such as in the case of the AI-powered fire detection system used by Tasmania's Fire Service.
- In the realm of data-and-cloud-computing, IBM and Cleveland Clinic have partnered to deploy a quantum computer dedicated to healthcare research, with the goal of using AI for biomedical discovery, emerging pathogen preparation, and drug optimization.
- Researchers at the Graduate School and University Center of the City University of New York have developed an AI system that can predict the efficacy of new drug compounds in humans, and this system was tested with approximately 9,800 patients.
- Snapchat has launched an AI-powered CPR teaching lens, providing users with a virtual human dummy and tips on the best speed and frequency of chest compressions for cardiopulmonary resuscitation. This innovation falls under the wider application of AI in technology and healthcare.
