3 AI Health Verticals Poised For Significant Growth
AI is transforming the healthcare landscape, driving innovation and efficiency across various sectors. As the technology evolves, three key AI-driven health verticals are poised to make significant strides in the next five years: Predictive Analytics for Disease Prevention, Diagnostic Imaging, and Personalised Medicine.
These areas not only promise to enhance patient outcomes but also to optimise operational efficiencies and resource management within healthcare systems.
By exploring the potential of AI in each of these verticals, we can better understand how these advancements will shape the future of healthcare, offering more precise, efficient, and personalised care solutions. Let’s delve into the transformative impact and growth opportunities in these critical areas.
AI in Predictive Analytics for Disease Prevention
Healthcare systems using AI-based predictive analytics have reported reductions in hospital readmissions and improved management of chronic diseases, as indicated by research from the Journal of Medical Internet Research.
A study published in Nature Medicine showcased that AI algorithms could predict the onset of diseases like diabetes and cardiovascular conditions with high accuracy, allowing for preemptive measures.
Market Growth and Impact
Predictive analytics driven by AI is a rapidly growing vertical. The market for AI in predictive analytics is forecasted to grow at a CAGR of 37.5% from 2023 to 2030, reaching an estimated market size of USD 14.94 billion by 2030.
Key Drivers of Growth:
- Early Disease Detection: AI can analyse health data to identify patterns and predict the onset of diseases before symptoms appear, enabling early intervention.
- Population Health Management: AI tools can assess risk factors across large populations, helping healthcare providers to implement preventive measures and reduce the incidence of chronic diseases.
- Resource Optimisation: Predictive analytics can optimise resource allocation in healthcare settings by forecasting patient admission rates and necessary medical supplies.
Key Companies
- KenSci
- Owkin
- Qventus
Opportunities
Explainable AI — the key challenge for AI predictive analytics is the understanding of how the AI came to the conclusions it has. Explainable AI is not unique to this vertical or even healthcare but is vital to verify important decisions that are the result of it’s analysis.
AI in Diagnostic Imaging
AI systems have demonstrated they can diagnose diseases from imaging data with accuracy comparable to that of healthcare professionals. More recent systems (not fully tested and available) are beating human assessors with error margins under 5% and far earlier detection.
Institutions like the FDA have approved several AI algorithms for diagnostic imaging, which has accelerated adoption in clinical practice.
The opportunity to compound the success of AI detection in medical imaging is the result of effective deployment and continuous reinforcement learning.
Market Growth and Impact
AI in diagnostic imaging is poised for substantial market growth over the next decade. According to market reports, the AI in medical imaging market was valued at approximately USD 1.01 billion in 2023 and is projected to grow at a compound annual growth rate (CAGR) of 34.8% from 2024 to 2030, reaching an estimated value of USD 14.2 billion by 2032.
Key Drivers of Growth:
- Enhanced Diagnostic Accuracy: AI algorithms can analyse medical images with high precision, reducing human error and significantly improving diagnostic accuracy.
- Efficiency and Productivity: AI tools can process large volumes of imaging data quickly, expediting diagnosis and treatment planning, which is crucial in time-sensitive medical conditions.
- Integration with Telemedicine: AI-powered imaging tools facilitate remote diagnosis and consultations, aligning with the growing trend towards telemedicine.
Key Companies
- AIRSMed SwiftMR
- Medic Vision iQMR
- Subtle Medical
Opportunities
Integration with Electronic Health Records (EHRs): Enhanced data interoperability can allow for more comprehensive patient diagnoses and treatment plans.
AI in Personalised Medicine
Personalised medicine is a paradigm shift from the traditional “one-size-fits-all” approach to a more customised healthcare model. Personalised medicine aims to provide the right treatment to the right patient at the right time, and AI plays a pivotal role in making this possible.
Studies have shown that personalised treatment plans developed using AI have improved patient outcomes in oncology, particularly in selecting targeted therapies for cancer patients.
Market Growth and Impact
The AI-driven personalised medicine market is also expected to see significant growth. Personalised medicine is predicted to grow at a CAGR of approximately 11.8% from 2021 to 2028, reaching a market valuation of USD 6.77 billion by 2028.
Key Drivers of Growth:
- Customisation of Therapies: AI algorithms can determine the most effective therapies based on a patient’s unique genetic makeup, improving treatment outcomes.
- Genomic Data Integration: AI can analyse vast amounts of genomic data to identify mutations and predict disease risk, enabling personalised treatment plans.
- Predictive Analytics: AI can predict patient responses to different treatments, thereby optimising therapeutic regimens and minimising adverse effects.
Key Companies
- Illumina
- Aitia
- Path AI
Opportunities
Data Quality — Poor data quality significantly hampers the advancement of personalised medicine, leading to inaccurate predictions, biased treatments, and suboptimal patient outcomes. To address these challenges, it’s essential to implement robust data cleaning, standardisation, and validation processes, ensuring datasets are diverse and representative.
Creating This Analysis
The investigation and assessment of these verticals were conducted alongside Animus AI’s Market Analysis App.
It is the only AI co-pilot built for knowledge workers in the health sector with 15 different focused apps to choose from.
You can try it here — Animus Health (animus-health.com)
