VERTICAL GENIAL ONE PAGER

AI and algorithms are run by data, and this patient data is hard to acquire and innterpret, leaving AI very limited development opportunities

Mis-diagnosis, for example, sometimes AI detects a false fracture, and sometimes it detects that there is not a fracture while there is

Sampling biases occur in data, causing the development of biased AI models and data sets causing what so called a digital marginalisation and exclusion

AI can be a nightmare in the long-run

of medical professionals stated that they need better predictability and insights into their operations

64%

+ Applications

With AI

Current

50%

33%

67%

50%

Physician's time spent on tadministrative tasks

Physician's time spent on treating patients

CAGR 40.51%

AI in Healthcare

SDG 3 Good Health and Wellbeing

What is AI in healthcare?

The application of tools involving Machine Learning, deep learning, virtual reality, and other technology elements to aid in medical settings

Personalized Medicine

Using big data and bioinformatics allows to study patient data more specifically and offer a more human-centric treatment approach

Drug Creation

AI helps in clinical trials by embedding analytics faster, calssifying genes, molecular functions,

AI aides in the prediction of pandemics/epidimics

AI helps in identifying species and receptors on cells that might begin a pandemic/epidimic