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Can AI Models Improve Diagnosis of Pancreatic Cancer?
By John Halamka and Paul Cerrato—Pancreatic cancer remains one of the most life-threatening malignancies because it is so difficult to detect in its earliest, most manageable stage. Recent developments in AI, however, suggest it may be possible to improve the diagnostic process.
By John Halamka and Paul Cerrato - AI-enabled algorithms can’t exist in an operational vacuum. To really benefit our patients, they need to be deployed with the help of an interprofessional team of experts and a set of “delivery science” principles that most developers are not aware of.
By John Halamka and Paul Cerrato - The latest proposed rules from CMS and FDA emphasize the need for a balanced, nuanced approach to digital innovation.
By John Halamka and Paul Cerrato - Challenging the status quo in technology and medicine can take a heavy toll, but history has demonstrated that it often yields measurable benefits for both clinicians and patients.
By John Halamka and Paul Cerrato - Smartphone-based applications may help detect atrial fibrillation, warn clinicians about worsening mental status, and improve the management of heart failure.
By John Halamka and Paul Cerrato - Every clinician knows that early detection is one of the most powerful tools we have in the war on cancer. Several computational tools are enabling us to make early detection a reality, at least in two specialties.
By John Halamka and Paul Cerrato - Two recent studies strongly suggest that sepsis predictive algorithms may in fact be ready for “prime time.”
By John Halamka and Paul Cerrato - A recent report points out that providers are not taking the necessary steps to secure the mobile devices connected to their network.
By John Halamka and Paul Cerrato - A growing number of studies show that drug/gene interactions can influence how patients respond to specific medications. But there are barriers that prevent the full implementation of pharmacogenomic testing into routine clinical practice.
Mayo Clinic recently welcomed seven more healthcare startups to its accelerator program. In exchange for an equity position in each startup, Mayo Clinic gives young digital health companies the opportunity to refine their AI models using its deidentified data sets and subject matter experts.
By John Halamka and Paul Cerrato - Concerns about algorithmic bias and poor performance of the models have made many stakeholders more cautious about using these digital tools in patient care. That’s about to change.
Mayo Clinic Platform_Accelerate has announced its second cohort of health tech startups, including national and international businesses. The program will help seven companies develop and validate their artificial intelligence-driven health care products or solutions and advance their business plans.
We expect that someday many important diagnosis and treatment decisions will be made or augmented by AI applications. Today we are in the early stages of achieving that objective.