AI in Healthcare

Overview

Intelligence is thinking and reasoning ability observed in humans. Artificial Intelligence is imparting this ability to machines.

No doubt, healthcare is an area where most of the developments have taken place to identify diseases, cure and finding measure to prevent future illness.?

Benefits of AI in Healthcare

Providing user-centric experiences

Using large datasets and machine learning, healthcare organizations can find insights faster and more accurately with AI, enabling improved satisfaction both internally and with those they serve.

Improving efficiency in operations

By examining data patterns, AI technologies can help healthcare organizations make the most of their data, assets and resources, increasing efficiency and improving performance of clinical and operational workflows, processes, and financial operations.

Connecting disparate healthcare data

Healthcare data is often fragmented and in various formats. By using AI and machine learning technologies, organizations can connect disparate data to get a more unified picture of the individuals behind the data.

WHO introduces 6 principles for AI as follows:

Six Principles to Ensure AI works for the Public Interest in all Countries.

To limit the risks and maximize the opportunities intrinsic to the use of AI for health, WHO provides the following principles as the basis for AI regulation and governance:

Protecting human autonomy

In the context of health care, this means that humans should remain in control of health-care systems and medical decisions; privacy and confidentiality should be protected, and patients must give valid informed consent through appropriate legal frameworks for data protection.

Promoting human well-being and safety and the public interest

The designers of AI technologies should satisfy regulatory requirements for safety, accuracy and efficacy for well-defined use cases or indications. Measures of quality control in practice and quality improvement in the use of AI must be available.

Ensuring transparency, explainability and intelligibility

Transparency requires that sufficient information be published or documented before the design or deployment of an AI technology. Such information must be easily accessible and facilitate meaningful public consultation and debate on how the technology is designed and how it should or should not be used.

Fostering responsibility and accountability

Although AI technologies perform specific tasks, it is the responsibility of stakeholders to ensure that they are used under appropriate conditions and by appropriately trained people. Effective mechanisms should be available for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms.

Ensuring inclusiveness and equity

Inclusiveness requires that AI for health be designed to encourage the widest possible equitable use and access, irrespective of age, sex, gender, income, race, ethnicity, sexual orientation, ability or other characteristics protected under human rights codes.

Promoting AI that is responsive and sustainable

Designers, developers and users should continuously and transparently assess AI applications during actual use to determine whether AI responds adequately and appropriately to expectations and requirements. AI systems should also be designed to minimize their environmental consequences and increase energy efficiency. Governments and companies should address anticipated disruptions in the workplace, including training for health-care workers to adapt to the use of AI systems, and potential job losses due to use of automated systems.?????

These principles will guide future WHO work to support efforts to ensure that the full potential of AI for healthcare and public health will be used for the benefits of all.