In a paper on'Artificial Intelligence in Nursing' presented jointly by Dr Ramesh M.Sc Phd, HoD Medical Surgical Nursing, St Paul's Hospital Millennium Medical College, Ethiopia, and Dr S. Indira, Dean of Narayana Nursing College, said AI offers three advantages over traditional methods -- the ability to quickly consider large volumes of data in risk prediction, increased intervention specificity (accurately flagging patients most at-risk) and automated adjustments in variable selection and calculation. "AI can help detect which patient features are most important in public health applications, allowing for more focused preventive interventions. "AI may more accurately predict fall risk without manual calculation and provide automatic warning systems," said Prof. Ramesh and Dr Indira. They have also highlighted the role of mobile health technologies (smartphones, smartphone apps, and wearable technologies) to help manage chronic illnesses by receiving and sending data directly between patients and care-providers, creating a comprehensive picture of the dynamic state of a patient's health in their everyday environments. According to the duo, sensor-based technologies, when placed in the home or hospital environment and used in combination, help nurses compose text and multimedia messages (for sharing photos and videos), measure body movement and collect weight, movement, and environmental (temperature, light, sound, air quality) data. In a paper on'Artificial Intelligence in Nursing' presented jointly by Dr Ramesh M.Sc Phd, HoD Medical Surgical Nursing, St Paul's Hospital Millennium Medical College, Ethiopia, and Dr S. Indira, Dean of Narayana Nursing College, said AI offers three advantages over traditional methods -- the ability to quickly consider large volumes of data in risk prediction, increased intervention specificity (accurately flagging patients most at-risk) and automated adjustments in variable selection and calculation. "AI can help detect which patient features are most important in public health applications, allowing for more focused preventive interventions.

Nellore: The conference on Futuristic Nursing being held at Narayana Nursing College here has discussed at length aspects of patient safety as also use of artificial intelligence and tele-medicine, apart from mobile health and sensor-based technologies (smartphones, smartphone apps and wearable technologies). More than 800 nurses are participating in the meet and around 40 eminent nursing leaders across the globe discussing the latest in nursing practices during the 3-day conference from Saturday. In a paper on'Artificial Intelligence in Nursing' presented jointly by Dr Ramesh M.Sc Phd, HoD Medical Surgical Nursing, St Paul's Hospital Millennium Medical College, Ethiopia, and Dr S. Indira, Dean of Narayana Nursing College, said AI offers three advantages over traditional methods -- the ability to quickly consider large volumes of data in risk prediction, increased intervention specificity (accurately flagging patients most at-risk) and automated adjustments in variable selection and calculation. "AI can help detect which patient features are most important in public health applications, allowing for more focused preventive interventions. Robots may aid nursing care tasks in hazardous clinical environments and they have the potential to automate some tasks."

The French national radiology congress (JFR) kicked off officially on Friday with a strengthened focus on artificial intelligence (AI) and machine learning. The discussion included an update on an ambitious project to create a national ecosystem in France for AI algorithm development. Dr. Jean-Paul Beregi, head of imaging at Nȋmes university hospital, updated delegates on the current status of France's new DRIM France IA imaging initiative, a nonprofit, independent AI ecosystem. The project has advanced significantly since it was announced last October, according to Beregi. The ecosystem now has a scientific committee and a charter, and is looking at how to move forward with institutional partners.

Reuters reports that artificial intelligence (AI) will play a key role in the advancement of diagnoses and treatments across the healthcare spectrum. Siemens Heathineers (OTCPK:SIEGY)(OTCPK:SMAWF) has leveraged AI to develop a digital twin heart that mimics the electrical and physical properties of real cardiac cells enabling surgeons to run simulations before surgery, to see if a pacemaker is appropriate for a particular patient, for example. Philips sells AI-enabled heart models that convert two-dimensional ultrasound images into data that helps physicians diagnose problems or automatically analyze scans to help surgeons plan operations. A shortage of doctors in China is stoking demand for AI tools to analyze medical images. Alibaba is one of the early leaders, using its cloud and data systems to develop AI solutions to analyze CT and MRI images.