Many adaptations to the coronavirus pandemic will remain standard features of health care long after the pandemic wanes, according to Brian Chapman, managing partner at ZS Associates, an Evanston, Ill.-based pharmaceutical and medical technology consultancy. In the long term, telehealth will be a clear winner as payers look to lower ongoing costs, more procedures and care will move out of hospitals, rapid diagnostics will gain importance, and government and payer coverage of infectious disease testing of all kinds will expand, he predicted.

The emergence of the new variety of coronavirus has had a massive effect on medical care across the globe, which has boosted telehealth coverage while suppressing non-emergency procedures. Several medical societies have published guidelines for procedures during the COVID-19 outbreak, however, which in the aggregate suggest that many procedures will be significantly delayed.

Palo Alto, Calif.-based Varian Medical Systems Inc. is no stranger to machine learning applications. It rolled out its first such software to guide photon-based radiotherapy treatment planning more than five years ago. Now, it’s expanding a similar approach for machine learning-driven patient matching and treatment guidance in proton treatment planning.

The U.S. Federal Communications Commission (FCC) has received funds for another telehealth program in less than a year. An agency statement indicates that the program “would immediately support health care providers” working to thwart the COVID-19 outbreak. This would be achieved in part by supporting purchases of devices and other items needed to provide telehealth, which the Connected Health Initiative said will help drive an overdue overhaul of health care in the U.S.

COVID-19 has disrupted science in the way it has disrupted everything else. In the short term, universities have largely closed shop as a way to maximize social distancing, and lots of science – or at least, lots of bench work – is not getting done.

The novel coronavirus pandemic has been managed with widely varying degrees of success around the world. Artificial intelligence (AI), which can help to power all sorts of efforts, has been enlisted thus far in limited ways. But researchers at a virtual conference held on April 1 by the Stanford Institute for Human-Centered Artificial Intelligence explored some of the ongoing and potential applications of AI to systematize efforts to fight COVID-19.

An artificial intelligence-based system can accurately detect COVID-19 using thoracic CT scans in patients with respiratory symptoms, according to a preprint study published on arXiv.org. The system can also help monitor patients with the disease. Other teams have employed AI to speed diagnosis and develop clarity on the signature appearance of the disease in the lungs of symptomatic patients.