AI May Have Defeated Another Superbug
As more medical teams leverage AI, scientists hope that solutions to persistent drug-resistant bacteria will appear more readily while reducing research
Topic: Healthcare
How the healthcare industry uses real-time analytics, including to monitor patients, save lives, and enable staff location-management in medical facilities. Predictive medicine applications are also explored.
AI Tool Detects Early Signs of Dementia
The team developing the CognoSpeak system demonstrated an accuracy of 90 percent in trial tests at predicting the Alzheimer’s
What Medical Device Teams Need Now: Service Co-Pilot
Medical device service organizations are experiencing growth while managing to keep costs in check, despite inflation and economic downturn negatively …
Healthcare Use Cases for Stream Processing
Stream processing and real-time responsiveness can significantly improve existing customer care processes and data
Deep Learning in Drug Discovery Holds Great Promise
Traditional techniques for medical data interpretation are often time-consuming and expensive. Deep learning offers a promising solution in drug discovery and …
Global eCOA Market: Strong Growth to Come
The global electronic clinical assessment outcome (eCOA) solution market will see increasing use of connected devices and the Internet of Things (IoT) over the …
Revolutionizing Healthcare with Generalist Medical AI
Generalist Medical AI models have the potential to revolutionize healthcare by providing advanced capabilities in medical diagnosis, decision support, and …
A Virtual You: Digital Twins will Sample the Medicine Before You Do
Supported by the power of artificial intelligence, digital twins can be deployed for preventive healthcare and other medical use
AI Now Protects the Most Vulnerable Patients
The new system uses AI-driven analytics, IoT sensors, and network connectivity to eradicate hazards in private rooms and public spaces by targeting a range of …
Researchers Use AlphaFold To Design Cancer Drug
Researchers from the University of Toronto have shortened the time it takes to develop a drug from years to a month with the use of DeepMind's