Predictive Analytics World for Healthcare 2022

Predictive Analytics World for Healthcare is organized by Predictive Analytics World (PAW) and will be held on Oct 06, 2022 at Radisson Collection, Berlin, Germany.

Description :
Machine and deep learning are the critical tools to handle the vast and ever faster-growing amount of healthcare data. That is why we are particularly pleased that the data science community will again meet in person in October in Berlin for the Predictive Analytics World for Healthcare 2022 conference to demonstrate successful applications of predictive analytics and to share deep knowledge about analytical and technical challenges. Meet experts from leading-edge companies and organizations and discuss current trends and challenges in health tech.

Why Attend:
Attend Predictive Analytics World for Healthcare and witness today’s rapidly emerging movement to fortify healthcare with big data’s biggest win: the power to predict. The premier cross-vendor networking event, this conference assembles the industry’s leaders to deliver case studies and expertise, revealing how predictive analytics:

• Improves patient care
• Reduces costs
• Brings greater efficiencies to the healthcare industry

Predictive analytics addresses today’s pressing challenges in healthcare effectiveness and economics by improving operations across the spectrum of healthcare functions:
Personalized medicine. Per-patient prediction and analytically enhanced diagnosis drive individual clinical treatment decisions
Insurance. Predictively guided decisioning combats risk and renders insurance more equitable and profitable
Hospital administration. Analytics detects and recoups loss due to fraud and waste
Healthcare marketing. From medical suppliers to healthcare screening service providers, the performance of industry enterprises hinges on analytically targeted marketing
Drug development. Analytics advances pharmaceutical engineering, testing, and other processes
Much more. Other applications include predicting per-patient disease progression, mortality risk, availability of clinical trial participants, consumer prescription adherence, and more