AI healthcare bottlenecks (and how to get through them)

These days, more and more healthcare providers are riding the wave of artificial intelligence (AI) innovation to provide better healthcare services. These include aiding drug discovery, predicting the risk of terminal diseases, developing novel drugs and using data-driven algorithms to improve the quality of patient care all with the support of AI-powered solutions. Pera Labs, for instance, claims to be a groundbreaking fertility company that uses AI and lab-on-a-chip technology to “help aspirational parents by assisting fertility clinics [to] reduce their standard 70% treatment failure rate.” For its part, HyperAspect deploys its AI solutions for tracking things like patient records and equipment providing healthcare facilities with comprehensive visibility of all their data, so they can make better decisions. NeuraLight’s AI-driven platform integrates multiple digital markers to accelerate and improve drug development, monitoring and precision care for patients with neurological disorders.

Medigy Insights:

Artificial intelligence is being used by healthcare providers to improve services such as drug discovery and patient care, but there are challenges including bias in data and concerns around AI ethics. To overcome these challenges, healthcare providers must address issues in the data pipeline and consider the ethical implications of using AI.