Category: AI

Recon takes an analytical look behind select developments in healthcare

AI for Pipeline Discovery and Beyond

“media attention [is] on lead identification, probably because it sells headlines” –  Greg Meyers, Chief Digital and Technology Officer, BMS[1] The biopharma industry is known for its high risk and potential high reward, but R&D costs have skyrocketed over the past century, delivering diminishing returns on investment. Despite breakthroughs, success rates remain low, and bringing a drug to market takes years. To combat this, the industry has continually adopted new tools, including crystallography, bioinformatics, robotics and high-throughput screening, all aimed at improving early-research efficiency and success rates. The latest tool generating

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Advances in AI for Health in 2021: An Analysis of the Clinicaltrials.gov Registry

The role of artificial intelligence (AI) and machine learning (ML) in healthcare spans a vast range of potential applications. A view of AI development on clinicaltrials.gov helps to focus this landscape, giving a sense of trends and near-term applications. Following last year’s review of AI development, we have updated our analysis to include registered studies starting in 2021.[1] The analysis revealed continued strong growth of studies across the field, especially in patient engagement and research. Within patient engagement, the tools studied (mostly chatbots) have increased in complexity, tracking with advancements

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Clinicaltrials.gov and AI-related studies: a brief status check in April 2021

Healthcare is by nature conservative; despite a huge level of interest for artificial intelligence (AI) and machine learning (ML) techniques, significant penetration in standard workflows of care will depend on demonstrations of safety and efficacy. As a result, it is today’s pipeline of clinical studies using AI/ML that will determine mainstream usage tomorrow.  In order to better understand this pipeline, we have mined clinicaltrials.gov for characteristics and trends of registered studies making use of AI/ML. Unsurprisingly we see strong growth, but starting from a very small baseline. Although most of

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