Generative AI - the new form of AI which could transform every major industry, leverages ML models and algorithms such as generative pre-trained transformer model for consolidating and producing content, which includes images, art and music. This happens in seconds from source across the internet.

While using generative AI tools such as ChatGPT for either writing essays or creating art without human assistance has been trending on social media & among students as well. It can also be used to write code without a data scientist too.

When it comes to healthcare, generative AI can identify breast cancer in radiology images through its ML algorithms for rendering patients with in-depth information regarding their diagnoses.

Generative AI possesses the potential to be a game changer that revolutionizes the healthcare ecosystem in numerous ways where we can only begin to predict today. It is highly essential that the healthcare organizations prepare for as well as understand the exciting possibilities these new technologies could have across the industry.

Four ways to leverage Generative AI in Healthcare

Personalized Medicine

Generative AI algorithms can analyze humongous amount of data which comprises social drivers of health and genomic data, for identifying patterns, predict outcomes & improve care and wellness. With these personalized medicine techniques, healthcare providers could easily customize more informed treatment plans to individuals, which in turn would increase the chance of success as well as reduce the risk of side effects or non-adherence. For instance, generative AI algorithms embedded with the most current practice guidelines, social drivers as well as health monitoring information that could serve as a "driver assist" for clinicians in order to help them analyze the complete health and generate recommendations for diagnosis, treatment & follow-up care. This helps the clinicians make more informed decisions.

Drug Development and Clinical Trials

Generative AI algorithms can be used in identifying potential targets for new drugs & predict what compounds are most likely to be effective by analyzing data from clinical trials as well as various other sources. Therefore, this could augment drug development, and potentially get new treatments to the market not just faster however at a lower cost as well. Furthermore, generative AI could also run compound data over genomic data to eliminate biases as well as pinpointing correlations which advance present treatment pathways.

Screening and Diagnosis

Generative AI algorithms would help in identifying chronic disease earlier in order to improve health outcomes by integrating data conventionally in the EHR with data from outside of the EHR like social determinants of health & social networking data. And, this would help healthcare providers to make more accurate & timely diagnoses leading to earlier treatment & better patient outcomes.

Predictive Maintenance

Generative AI algorithms would predict when maintenance is required by analyzing data from medical devices, that include imaging equipment/ventilators and this will help healthcare providers in activating their supply chain processes prior to proactively maintain their equipment & decrease the risk of equipment failure.

The Complex Opportunity to advance Generative AI in healthcare

Although generative AI shows promise in advancing healthcare, the complex capabilities of it would lead to concerns & one of this being the potential for bias in the algorithms that could result in unequal access to care/discrimination against certain groups of patients. Making sure that generative AI algorithms are trained on diverse as well as representative datasets will be crucial to mitigate these risks.

The next challenge is the requirement for regulatory frameworks for ensuring the safety as well as effectiveness of generative AI in the healthcare segment. Building these frameworks would need collaboration among industry, regulators & other stakeholders & will be crucial for ensuring that generative AI is leveraged responsibly as well as ethically.

By focusing on the following, forward-thinking healthcare firms will be able to take advantage of generative AI technology:

Building a data infrastructure: Healthcare firms will need to integrate large, diverse as well as high-quality datasets in order to completely leverage the caliber of generative AI & this will need investments in a data infrastructure, that comprise the data architecture, storage, management as well as analysis tools.

Partnering with AI experts: The payers, healthcare providers, as well other firms would not have the in-house expertise for building & implementing generative AI solutions. Collaborating with AI experts that include AI startups or consulting firms can help them to accelerate & access the expertise that is required for implementing generative AI projects successfully.

Training & educating staff: Healthcare firms will have to ensure that their staffs understand technology & how it can be implemented in order to completely leverage the potential of generative AI. Rendering training as well as change management support on generative AI can help the staff in understanding their capabilities & limitations so that they can integrate these new capabilities into established workflows.

Although generative AI is complex it is the capability the healthcare sector has been waiting for. Generative AI could be the solution to digital transformation in healthcare if leveraged appropriately. In other words, it brings together disparate sources of data in seconds for creating meaningful insights which reduce the burden of the end user.