Research

Integrating Digital Twins and Deep Learning for Medical Image Analysis in the Era of COVID-19

Digital twins are virtual representations of devices and processes that capture the physical properties of the environment and operational algorithms/techniques in the context of medical devices and technologies. Digital twins may allow healthcare organizations to determine methods of improving medical processes, enhancing patient experience, lothis studyring operating expenses, and extending the value of care.

AI Approach may Help Identify Melanoma Survivors who Face a High Risk of Cancer Recurrence

Most deaths from melanoma - the most lethal form of skin cancer - occur in patients who were initially diagnosed with early-stage melanoma and then later experienced a recurrence that is typically not detected until it has spread or metastasized.

A team led by investigators at Massachusetts General Hospital (MGH) recently developed an artificial intelligence - based method to predict which patients are most likely to experience a recurrence and are therefore expected to benefit from aggressive treatment.

Telemedicine Reduces Odds of No-Show Clinic Visits by More than Two-Thirds for Surgical Patients

Surgical patients who use telehealth services are much more likely to show up for their initial clinic visit or follow-up appointment during the post-surgery period than those who rely on in-person visits only. Research findings were presented at the Scientific Forum of the American College of Surgeons (ACS) Clinical Congress 2022.

Can Smartphones Predict Mortality Risk?

Passive smartphone monitoring of people’s walking activity can be used to construct population-level models of health and mortality risk, according to a new study publishing October 20th in the open access journal PLOS Digital Health by Bruce Schatz of University of Illinois at Urbana-Champaign, USA, and colleagues.

A New AI Model can Accurately Predict Human Response to Novel Drug Compounds

The journey between identifying a potential therapeutic compound and Food and Drug Administration approval of a new drug can take well over a decade and cost upwards of a billion dollars. A research team at the CUNY Graduate Center has created an artificial intelligence model that could significantly improve the accuracy and reduce the time and cost of the drug development process.

Telemedicine Program Halves Time to Treatment

When struggling to conceive, every second that ticks by feels precious. That makes it easy to get discouraged: 65 percent of those who seek fertility care eventually discontinue treatment, the majority due to stress. That's why Penn Medicine recently instituted a telemedicine-driven program aimed at seeing patients more quickly and starting treatments sooner.

Repurposing Existing Drugs to Fight New COVID-19 Variants

Michigan State University (MSU) researchers are using big data and AI to identify current drugs that could be applied to treat new COVID-19 variants.

Finding new ways to treat the novel coronavirus and its ever-changing variants has been a challenge for researchers, especially when the traditional drug development and discovery process can take years.

Research News

Integrating Digital Twins and Deep Learning for Medical Image Analysis in the Era of COVID-19

AI Approach may Help Identify Melanoma Survivors who Face a High Risk of Cancer Recurrence

Telemedicine Reduces Odds of No-Show Clinic Visits by More than Two-Thirds for Surgical Patients

Can Smartphones Predict Mortality Risk?

A New AI Model can Accurately Predict Human Response to Novel Drug Compounds

Telemedicine Program Halves Time to Treatment

Repurposing Existing Drugs to Fight New COVID-19 Variants

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