This topic focuses on the use of AI in medicine, medical care, health insurance, diagnostics, pharmaceuticals and health-related sensors.
Healthcare has undergone consistent changes. From surgeries that were conducted by sedating patients with opium and amputation of an infected part, the technology has evolved… Read More »Enhancing patient care with AI-powered health monitoring and remote patient management
There is no denying that data is easily one of the most valuable resources globally. But what’s interesting are its applications, in addition to driving… Read More »Healthcare Analytics: How it Enables Better Patient Care
Machine learning in Healthcare industry.
The healthcare sector is a complex ecosystem consisting of different stakeholders- patients, hospitals, physicians, healthcare staff, pharmacies, and laboratories. As one of the most restricted… Read More »Exploring the Benefits of Big Data Analytics in Healthcare
Delve into digital healthcare trends and examine how automated data entry is revolutionizing patient data management, decision-making, and care delivery.
The world is going digital at a very fast speed. From retail shops to the cab industry to banking, all are changing and so is… Read More »Top Healthcare App Development Trends That Will Dominate 2023
A digital twin in healthcare is a virtual representation of human physiology, hospital results, lab environment, etc. It is revolutionizing hospital management and clinical healthcare… Read More »Digital Twin Technology – Top Use Cases in Smart Healthcare
As artificial intelligence (AI) becomes an increasingly important tool in health care, it offers unprecedented opportunities for improving patient outcomes, reducing costs, and impacting population… Read More »Training Data to Employ AI in Healthcare
Wearable devices are gadgets that can comfortably be worn on a body. These devices have intelligent sensors connected to the internet for collecting data. The… Read More »AI Enable Wearable Devices: The Next Layer of IoT and Machine Learning
Artificial intelligence (AI) and machine learning (ML) have received widespread interest in recent years due to their potential to set new paradigms in healthcare delivery. It is being said that machine learning will transform many aspects of healthcare delivery, and radiology & pathology are among the specialties set to be among the first to take advantage of this technology.
