One driver of increased pharmaceutical spending is the high failure rate of expensive and time-consuming randomized control trials. deepDTnet, a network-based deep learning methodology for novel target identification and in silico drug repurposing, may aid in the development of novel, effective treatment strategies for complex diseases.
Technology-enabled data capture is accelerating progress in biomechanics and in the care of neurological disorders. A leading researcher shares insights on some of the advances in a new podcast episode.
Progress toward use of machine learning and deep learning techniques to inform epilepsy surgery decisions for individual patients is well underway. We share a status report on Cleveland Clinic’s experience in this space.
Cleveland Clinic researchers have trained an advanced computer network to find subtle radiation sensitivity features in the CT scans of individual lung cancer patients that can predict the likelihood of successful radiotherapy outcomes. The network can generate a personalized radiation dose plan that reduces the probability of treatment failure to less than 5%.
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Machine learning can be applied to osteoarthritis gait models and joint-specific imaging analysis to identify opportunities for optimization across the care continuum.
A proprietary remote patient monitoring system—with smart knee sleeve—motivates patients while collecting outcomes. Dr. Brendan Patterson explains the recent feasibility study and how it might help establish the value of total knee arthroplasty.
Cardiothoracic surgery has benefited from leading-edge data science methods more than almost any other specialty. We look back and forward with one of the giants of the field, Dr. Eugene Blackstone.
A new multidisciplinary center will concentrate efforts to use artificial intelligence to improve healthcare delivery in areas such as diagnostics, disease prediction and treatment planning.
A validated machine learning tool accurately predicts the orthopaedic episode of care, building payment models that account for patient-specific risk and comorbidities.
Why Cleveland Clinic is turning to AI to help guide spine care decision-making, and insights from an early analysis of how AI would have improved care of a historical patient cohort.