Health venture architects and entrepreneurs are breaking new ground in the healthcare industry with smart healthcare systems that are making AI health tech even more prevalent.
Advances in AI, such as machine learning, natural language processing and computer vision are bringing about life-changing innovations. From robot-assisted surgeries to virtual nurses and workflow assistants, AI is definitely enhancing healthcare. In the first part of this article we wrote about how AI is driving changes in health tech.
However, as medical AI matures, it has come up against a few checkpoints. Future health tech leaders will have to address these obstacles to enable smoother adoption.
AI roadblocks to overcome in the healthcare industry
For AI in healthcare to reach its potential, it will need to reconcile these challenges:
Prolific use cases of specific AI applications - One hiccup surrounding healthcare AI is the lack of case studies that would go a long way in presenting the case for AI adoption.
Cybersecurity for medical AI - The medical field is a favorite hacker target. Ensuring data protection and privacy will strengthen AI adoption.
AI applications that enable HITRUST compliance - As private patient information moves across databases in an AI ecosystem, it will become necessary for AI solutions to become HIPPA, FTC, PCI compliant to enable medical institutions to maintain HITRUST certification.
Permanent changes AI will bring to the future of healthcare delivery
As AI applications learn from experiences in the field, they will continue to deliver more precise results, along with the added benefits of cost reduction, more diverse solutions, and further reach.
Diagnosis and treatment recommendations will become more accurate. Almost assuredly, radiology and pathology will fall nearly entirely within the purview of AI. And aided by improvements in speech and text recognition, AI will take over patient communications and clinical notes.
AI in healthcare will also be subjected to greater regulations, standardization, and governance. This, along with training people in AI, will lead to widespread adoption in the healthcare industry.
Just as AI needs to interface with other applications and infrastructures to function in the healthcare ecosystem, so it needs to synergize with the humans using it.
According to research from the Future Healthcare Journal, “It seems increasingly clear that AI systems will not replace human clinicians on a large scale, but rather will augment their efforts to care for patients. Perhaps the only healthcare providers who will lose their jobs over time may be those who refuse to work alongside artificial intelligence.”
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