This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
An important part of advancing medical research and drugdevelopment is making participation in clinical trials easier and more inclusive. To develop treatments that work on men, women, and children of all ages and different ethnicities we need to have clinical trial data that represents our diverse population.
Artificial Intelligence is utilized in various areas of healthcare, ranging from drugdevelopment to medical image analysis. By examining vast amounts of patient data, healthcare professionals can recognize risk factors, predict outcomes, and develop personalized treatment plans.
Drug Discovery: Example: An SLM can analyze vast amounts of scientific literature to identify potential drug targets, predict drug interactions, and accelerate the drug discovery process. Benefit: Reduces research costs, speeds up time-to-market for new medications, and improves the success rate of drugdevelopment.
Furthermore, by fostering connectivity and automating tasks, DHTs reduce administrative burdens, accelerate recruitment, and improve overall trial transparency, ultimately contributing to faster and more reliable drugdevelopment.
Some of the key trends in healthtech evolution include: The rise of digital health: Digital health is the use of technology to deliver healthcare services remotely. This includes telehealth, mobilehealth apps, and wearable devices.
It monitors a patient’s health, wellbeing and safety from a distance to reduce the risk of disease transmission, connects family members with patients during isolation, and establishes safe zones with geo-fencing to be notified when a patient has left their quarantine zone.
Technology continues to play a large role in healthcare, expediting and reducing the costs associated with the drugdevelopment process. The implementation of AI has been instrumental in significantly cutting down the drugdevelopment timeline and creating viable drug targets in a more timely and cost-efficient manner.
We organize all of the trending information in your field so you don't have to. Join 48,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content