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May 26 2025
8Artificial intelligence (AI) is gaining broader application in healthcare, moving far beyond its well-known role in expediting drug discovery. While AI has already proven valuable in helping pharmaceutical companies and biotech startups identify new molecules for clinical testing, its true impact may be in areas that have traditionally relied heavily on human labor and judgment.
Liz Beatty, chief strategy officer at clinical trials technology firm Inato, highlighted the persistent bottlenecks in the clinical trial process. “Even if a drug is discovered rapidly, it still must be tested in people,” she explained. Drawing from her 16 years of experience overseeing clinical trials at Bristol Myers Squibb, Beatty noted that over 80% of trials miss deadlines, largely due to difficulties in enrolling eligible participants.
Historically, assessing patient eligibility involved manually reviewing extensive medical records, often spanning hundreds of pages. Inato’s AI platform addresses this inefficiency by automating the review process. While final decisions about trial enrollment still rest with human professionals, the platform reduces the evaluation time from hours to mere minutes. “We’re finally able to use AI on a critical pain point in research that couldn’t be tackled before recent advancements,” Beatty said during a panel discussion at the MedCity News INVEST conference in Chicago.
The panel, titled “How Is AI Reshaping the Healthcare Industry,” featured additional insights from Chelsea Vane, vice president of product management for digital products at GE Healthcare, and Bobby Reddy, co-founder and CEO of Prenosis. The session was moderated by Michelle Hoffmann, executive director of the Chicago Biomedical Consortium.
AI applications are also being integrated into direct patient care. Prenosis, for example, has developed a diagnostic tool called Sepsis Immunoscore to aid clinicians in identifying sepsis — a potentially deadly condition that occurs when the body overreacts to infection, causing inflammation and organ failure. Traditionally, diagnosis has relied on physician judgment, often leading to variability in outcomes.
Sepsis Immunoscore uses AI to analyze a range of inputs, including vital signs, lab results, demographic details, and biomarkers, to better understand patient biology. Reddy emphasized that sepsis is not a single illness but a syndrome composed of multiple disease processes. The AI-driven tool offers standardized insights based on data from thousands of previous cases, making the diagnosis more accurate and consistent. The technology received De Novo authorization from the FDA last year, marking it as the first AI-based diagnostic device for sepsis.
GE Healthcare is also leveraging AI to enhance access to medical imaging and cancer care. Vane cited AIR Recon DL, a deep learning tool that reconstructs MRI images by removing noise and distortion. This results in higher-quality images and reduces scan time by up to 50%, enabling providers to serve more patients. Similar AI capabilities are also being deployed for CT imaging.
In oncology, GE’s CareIntellect platform aggregates various types of patient data—from imaging to electronic health records—into a unified interface. This allows clinicians to quickly review a patient's complete medical history without switching between systems. The tool not only summarizes complex records in minutes but also supports clinical trial eligibility assessments.
“By combining and summarizing all this multimodal data, we’re not only speeding up the clinician’s review process but also giving them more time to focus on the patient,” Vane said.
From streamlining research and clinical trials to enhancing diagnostics and imaging, AI is poised to make healthcare delivery more efficient, consistent, and patient-focused.
Source:https://medcitynews.com/2025/05/ai-is-finding-broader-use-in-in-healthcare-and-its-not-just-for-speedy-drug-rd-anymore
This is non-financial/medical advice and made using AI so could be wrong.
