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Excerpt: Understanding and Building a Skill Set for Machine Learning with Drug Dosing

In this excerpt from a recent Journal of AHIMA article, Shannon Houser and R. Jeffrey Harris discuss the special skill sets needed when working with machine learning in drug dosing applications.

A subset of artificial intelligence, machine learning (ML) is widely applied in healthcare, including pharmacy practices. It can be used to calculate dosages in special populations that are difficult for traditional human computing.

woman taking pills

Excerpt: Understanding and Building a Skill Set for Machine Learning with Drug Dosing

In this excerpt from a recent Journal of AHIMA article, Shannon Houser and R. Jeffrey Harris discuss the special skill sets needed when working with machine learning in drug dosing applications.

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Impact Area: Workforce

AHIMA22 Global Conference will be a great opportunity for members to hear from a variety of experts regarding the workforce. There will be top industry leaders providing relevant and realistic takeaways in automation, managing teams in remote environments, and career opportunities.

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AHIMA22 Impact Area: Privacy and Security

AHIMA22 Global Conference has top experts on information blocking, electronic health record vendor efforts to protect privacy and achieve interoperability, cyberthreats, and risks associated with the Internet of Medical Things (IoMT).

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Impact Area: Data

AHIMA22 Global Conference is an opportunity to hear from industry experts on topics focused on the impact of health data in the healthcare industry. Look forward to hearing the incredible stories of successes and challenges organizations face in the realm of health data.

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Impact Area: Consumerism

We’re experiencing a turning point in healthcare, with consumers finally empowered to make more informed decisions about their health. AHIMA22 includes a focus on consumerism because these sessions offer incredible insight for health leaders to learn about new and emerging technologies and roles in health information that place the patient at the center of it all.

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