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.

Nearly one in six young women who suffer a heart attack can’t be classified under the Fourth Universal Definition of MI, according to a study out of Yale University—but the majority can be accurately classified using a sex-specific taxonomy known as VIRGO.

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.

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.

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.

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.  

Cardio-oncology has emerged as an area of rapid growth in the medical community in recent years, owing in large part to an increasing population of cancer survivors.