Machine Learning Pharmaceuticals Technical Review 
TechCrunch
JULY 20, 2021
Some technologies have helped deal with this menace; for instance, radio frequency identification, which works by assigning serial numbers to containers of each product. More modern approaches are being adopted these days, which is the case of RxAll , a startup using deep technology to provide quality medication to patients.
OTS Solutions
JUNE 3, 2022
Technology has proven important in maintaining the healthcare industry’s resilience in the face of so many obstacles. The healthcare business has embraced numerous technology-based solutions to increase productivity and streamline clinical procedures. The intelligence generated via Machine Learning.
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CIO
SEPTEMBER 18, 2023
When the timing was right, Chavarin honed her skills to do training and coaching work and eventually got her first taste of technology as a member of Synchrony’s intelligent virtual assistant (IVA) team, writing human responses to the text-based questions posed to chatbots.
CIO
OCTOBER 1, 2024
In an era of major technology shifts and business disruptions, CIOs are better prepared to help their companies navigate possible delays due to the port strike but settling the impasse is of great concern, observers claim, as a protracted strike could have widespread impact on organizations across a range of industries.
TechCrunch
OCTOBER 29, 2020
The company’s machine learning dashboard is able to detect improper payments more quickly, conduct clinical claim reviews and generate reports, speeding up and cleaning up a process that’s been mostly manual and inefficient. Alaffia automates the process of auditing health insurance claims.
CIO
JUNE 7, 2022
But the success of their AI initiatives depends on more than just data and technology — it’s also about having the right people on board. They process and analyze data, build machine learning (ML) models, and draw conclusions to improve ML models already in production. Data scientists are the core of any AI team.
CIO
NOVEMBER 4, 2022
For pharmaceutical companies in the digital era, intense pressure to achieve medical miracles falls as much on the shoulders of CIOs as on lead scientists. Rigid requirements to ensure the accuracy of data and veracity of scientific formulas as well as machine learning algorithms and data tools are common in modern laboratories.
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