The healthcare sector experienced transition as a result of COVID-19, and this shift will last for years to come. Despite industry obstacles, the pandemic has led to a growing acceptance of new technology among patients, providers, and healthcare practitioners. These technologies lessen workplace stress and improved patient care. But there is still hope for change. Many medical schools now include the use of technology in their curriculum; the new generation of medical practitioners has a distinct relationship with technology.

A wide range of nanomedicines exist, many of which revolve around being the'carrier'. This means that they act as a vessel that can carry therapeutic payloads (a drug of interest) and deliver them to a specific location. This has become particularly useful for delivering drugs that would otherwise be too toxic to administer on their own. There are other nanomedicines as well, such as nanoparticles that can kill cancer cells and nanoforms of drugs that are in solid nanoparticle suspensions. These are but a few examples, and because nanomedicines span many areas from the'drug' itself to being a carrier, to being either inorganic or organic in nature, there are many things to think about when it comes to designing new nanomedicines.

Whether it's information-sharing between patients and doctors or aiding in a high-risk surgery, it's clear that dynamic applications of technology are well underway in disrupting the healthcare industry. Today's infographic from the Online Medical Care highlights healthcare areas where tech is breaking barriers. Artificial intelligence will have a dramatic impact on many industries, and healthcare is no exception. A large share of healthcare executives are already applying artificial intelligence in their operations, with data showing plans to increase budgets last year. As the technology becomes more developed and widespread, it's expected that AI could help diagnose strokes, eye disease, heart disease, skin cancer, and other conditions.

Personalized cancer medicine has advanced from a distant hope to a clinical reality. Oncologists regularly individualize treatments to target a tumor's unique genetic weaknesses. But because these personalized medicines reach healthy tissues and tumors alike, even the most targeted treatments can cause unwanted side-effects. A new approach devised by nanotechnology experts at the Sloan Kettering Institute (SKI) at Memorial Sloan Kettering Cancer Center may improve the precision of personalized medicines by helping them avoid collateral damage. "We found a way to use machine-learning algorithms to design powerful nanomedicines that can deliver a stronger, safer, more personalized punch," says Daniel Heller, PhD, a chemist in the molecular pharmacology program at SKI and an assistant professor at the Weill Cornell Graduate School of Medical Sciences.