In 2021, Artificial Intelligence funding rose 108%, with healthcare accounting for a fifth of this total, according to CB insights. The market size of the healthcare AI market reached $7 billion last year. By 2030, that figure might reach about $215 billion. The adoption of AI in healthcare is taking place on many fronts, from precision medicine and robotic surgery to machine learning for critical research or disease surveillance. Here we mention a few companies that are doing important work to advance health using AI.
Improving medical diagnosis
Diagnosis is not without human error: overwhelming caseloads and incomplete medical histories lead to mistakes. Fortunately, AI can frequently predict and diagnose faster than healthcare professionals.
Caption Health’s AI platform uses artificial intelligence and ultrasound technology for early disease identification. Ultrasound is a highly effective diagnostic tool, but it can be difficult to master and image quality can vary. Now, thanks to AI, any healthcare professional can capture and interpret digital-quality ultrasound images for a range of clinical applications. It’s currently used for cardiac images, but there are plans, with a grant from the Bill & Melinda Gates Foundation, to develop AI guidance and interpretation for lung ultrasound.
This company collaborates with medical experts to transform their ideas, knowledge and images into world class AI solutions. From organ detection to advanced decision support, Robovision helps create and deploy image-based AI applications that become digital assets for the medical professionals who developed them.
Ramping up drug discovery
Developing drugs is slow and expensive. To put a new drug through a clinical trial costs in the region $1.3 billion and many are still unsuccessful. AI can improve the process.
Using their AtomNet technology, Atomwise is a pharmaceutical company that uses AI to revolutionise how drugs are discovered. The company has tackled over 600 unique diseases, including Ebola and multiple sclerosis.
AtomNet, the company’s award-winning neural network, helps predict bioactivity and identify patient characteristics for clinical trials. Built using AI and Machine Learning (ML), the AtomNet platform enables massive scale and unprecedented speed - 100 times faster than traditional pharmaceutical companies - to create pipelines of new drugs.
Transforming patient experience
AI technology helps medical facilities streamline patients’ journeys by managing multiple data points more efficiently.
This preventative health technology provides an accessible and affordable health service for everyone. By combining human expertise and technology, their suite of tools, using AI, offers 24/7 access to doctors, personalized care plans and advisors, referrals to specialists, digital health tools and chronic disease management.
This digital therapeutic platform treats chronic pain via live physical therapists and a personalized therapy plan, including exercise routines, relaxation activities and learning resources . Their multimodal approach addresses the biological, psychological and social components of pain to offer a holistic solution.
In addition, using AI and smartphone capacities, the platform delivers automated, real-time feedback on an individual’s performance.
Improving patient outcome
90% of hospital data is not used - instead, it’s locked away in scattered and unstructured data sources. Lynxcare changes that. The Belgium-based company mines structured and unstructured hospital data, via an AI-powered platform, to improve patient outcomes and make real-world data accessible for life science research. To date, the platform has been used to detect rare diseases in order to speed up early diagnosis, analyse the effectiveness of new medication for cardiac failure, better understand the impact of specific cancer therapies, and better treat hospitalized Covid-19 patients.
Changing the practise of surgery
AI is transforming the surgery experience by advancing imaging, navigation and robotic intervention.
This company uses AI to improve the operating room (OR) experience by modelling a digital twin of OR operations. Their platform, combining data capturing, analytics, and a predictive data model, assists hospitals in reducing fatigue of surgical teams, increasing surgery volume and reducing total costs.