Options are increasing for healthcare consumers looking to check their symptoms with an AI digital platform for self-diagnosis. However, research into the use, accuracy and regulation of these technologies is woefully scant.

A pilot that aims to study the use of blockchain-enabled data technology to track and verify specialty prescription drugs has been approved by the FDA.

Researchers are looking into whether live and automated text messaging augmented by AI can help treat or ward off postpartum depression for women in Kenya.

A Harvard undergrad has created a computer program that can improve the treatment of tuberculosis, an infectious disease with unique challenges thanks to its shapeshifting ability to resist drugs.

If AI is to find a foothold across the worldwide healthcare ecosystem, it will need to rest on research into how it may affect the emerging realm of participatory medicine.

A machine-learning algorithm has surpassed four commonly used methods for catching sepsis early in hospital patients, giving clinicians up to 48 hours to intervene before the condition has a chance to begin turning dangerous.  

The boom in the emergence of AI and other innovative technologies in the healthcare space comes with a new risk: the expense of human contact.

Blockchain technology is already expected to have a major impact in the healthcare space, and the wearables sector could do with an injection of the technology, as well, writes Lucas Mearian for ComputerWorld.