Investments in the global healthcare industry have ramped up sharply since the COVID-19 pandemic. With the advent of artificial intelligence (AI), the industry witnessed a rapid transformation in early disease detection, genomic research, drug discovery, clinical processes, and treatment efficacy prediction.
According to a 2023 PwC report, the AI market in healthcare was valued at $11 billion and is expected to grow to $188 billion by 2030. On January 21st, Oracle Co-founder Larry Ellison said during a White House speech that AI plays an integral role in early cancer detection and vaccine development. He highlighted how AI could help detect tiny tumor fragments and assist in gene-sequencing malignancies for the development of mRNA vaccines at a rapid speed for customized cancer treatment options.
Furthermore, AI is speeding up accurate decision-making by aligning big health data with pattern recognition systems, improving patient outcomes by ensuring timely clinical intervention.
During a fireside chat at the annual J.P. Morgan Healthcare Conference on January 13th, Mayo Clinic chief administrative officer Christina Zorn shared how the company addresses potential future healthcare worker shortages and improves cancer care by leveraging AI in robotics and pathology database management.
“We’re going to use, essentially, the robots to be a member of the healthcare team in the healthcare spaces,” she said. “We saw a paradigm shift in healthcare. You’re either going to disrupt from within, or you’re going to be disrupted,” she said.
The significant growth potential in the evolving AI healthcare industry is driving investor interest in the sector as drug discovery and development companies continue to announce new-gen breakthroughs.
For this article, we selected AI stocks by reviewing news articles, stock analysis, and press releases. We listed the stocks in ascending order of their hedge fund sentiment taken from Insider Monkey’s database of 900 hedge funds.
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A robotic arm picking up a product assembly line, displaying the company’s consumer healthcare and wellness offerings.
10. Absci Corporation (NASDAQ:ABSI)
Number of Hedge Fund Holders: 20
Absci Corporation (NASDAQ:ABSI) is a drug discovery company that utilizes generative AI, reverse immunology, and proprietary synthetic biology tech in its drug-creation platform to rapidly identify antibodies produced by super immune responders for AI optimization for development of best-in-class candidates for ailments such as Inflammatory Bowel Disease. The company claims it takes six weeks to go from generating AI-designed antibodies to producing wet lab-validated candidates.
On January 22nd, Needham initiated coverage of Absci Corporation (NASDAQ:ABSI) with a “Buy” rating and a stock price target of $9. Needham analyst Gil Blum noted that the company’s ability to rapidly develop large-scale, indication-agnostic datasets for biologics using its high-throughput platform helps lower downstream clinical failures. Blum added that Absci Corporation’s (NASDAQ: ABSI) value lies in its ability to build in-house proprietary assets and monetize clinical-stage assets through partnerships with leading pharma companies for milestone payments and royalties rather than directly handling commercialization for steady income.
9. Medtronic (NYSE:MDT)
Number of Hedge Fund Holders: 60
Medtronic (NYSE:MDT) designs and manufactures medical devices as well as develops healthcare technologies and therapies for 70-plus health conditions involving cardiovascular, neuroscience, diabetes, orthopaedics, and urology. The medical devices leader is leveraging AI to enhance clinical decision-making, devise new indicators, and deliver customized treatment options.
On January 17th, Medtronic announced that its DEFINE AFib clinical study of 973 patients involving the company’s LINQ family of insertable cardiac monitors and AI-based algorithms helped detect atrial fibrillation (AF) episodes and identify high-risk participants with 80% accuracy. The study will enable researchers to refine AI and machine learning algorithms to predict the requirement of AF-related healthcare for individuals at high risk and ensure ideal treatment decisions.
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