Oncology diagnosis including digital pathology, telehealth and physician access are just some of the areas where AI can have outsize impact in 2021

Copyright by www.medcitynews.com

SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningApart from efforts to develop vaccines for Covid-19, 2020 has been a year of substantial advancements in artificial intelligence (AI) and machine learning – technologies that are being applied in healthcare as never before, resulting in improvements and enhancements in diagnosis and treatment that were previously impossible.

These technologies are advancing at an increasing rate, and we can be sure that AI will be used even more to overcome healthcare challenges in 2021 and beyond. Here are some of the main areas AI will be used to enhance digital healthcare in the near future.


Many healthcare practices today, including cancer diagnosis, still rely heavily on manual activities and processes – and even those that do utilize digital technologies use them on an independent basis, not under one integral environment. Pathology, the medical specialty of diagnosing disease in patients, most notably cancer, is a good example. Traditional pathology involves manual processes that have remained unchanged for years, where glass slides with tissue samples are analyzed by pathologists using microscopes.

But that is changing today with a growing trend of moving toward digitized infrastructures and workflows (for example digital pathology). This trend is expected to accelerate as a result of the Covid-19 pandemic, increasingly saving time and labor costs while providing better and more cost-effective care. Moreover, adding an AI layer to an already digitized workflow can help make processes even more efficient on several fronts, including:

Triage: AI tools can help determine which cases should be reviewed more urgently and which physicians or resources to assign to them. This will ensure that each case is diagnosed by the physician whose capabilities can best be applied to the situation at hand, assigning cases based on a physician’s sub-specialty or level of experience, which becomes especially important in complex cases.

Diagnosis: AI tools can also help with cancer diagnosis and assessment, pointing instantly to particular areas of interest, for instance those that include cancerous cells, and signaling the ‘needle in the haystack’ factor that can shed light on a patient’s situation – and what may be required to treat them. As a result, turnaround times for case reporting to the referring physician can be reduced significantly. In addition, smart AI tools will allow for the automation of some diagnostic tasks that are currently performed manually, such as counting cells, measuring features and automatically filling up parts of the report. […]

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