Artificial Intelligence

Review on Artificial Intelligence Healthcare Specialization


Artificial Intelligence

Analytics Insight presents the review on AI healthcare specialization

Artificial intelligence (AI) has revolutionized sectors all over the world, and it has the potential to completely disrupt the field of healthcare. Consider being able to analyze data on patient visits to the health center, medications prescribed, laboratory tests, and surgery done, as well as data from outside the health system like as social media, credit card transactions, census data, and web search activity logs containing valuable health information to have a sense of how AI could transform care for patients and diagnosis and treatment.

You will examine the present and future uses of AI in healthcare in this specialization, with the objective of understanding how to integrate AI technology into the clinic safely and ethically. This specialty is intended for both healthcare practitioners and computer science experts, and it provides insights to help the disciplines collaborate more effectively.

 

How does it work?

Take Courses

Coursera has a group of courses designed to help you master a specific skill. To begin, register in the Specialization directly or examine its courses and select the one you want to begin with. When you enroll in a course that is a component of a Specialization, you are immediately enrolled in the whole Specialization. It’s fine if you just finish one course; you may suspend your study or cancel your subscription at any moment. To keep track of your course registrations and progress, go to your learner dashboard.

 

Hands-on Project

A hands-on project is included in each Specialization. To complete the Specialization and get your certificate, you must successfully complete the project(s). If there is a separate program for the hands-on project in the Specialization, you must first finish all of the other programs before commencing the hands-on project.

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Earn a Certificate

When you complete all of the courses and the hands-on project, you will receive a Certificate that you can publish with potential employers and your professional network.

 

5 Courses in AI Healthcare Specialization

Course 1: Introduction to Healthcare

• Rating: 4.8 stars

Solving the difficulties and challenges inside the United States’ healthcare system necessitates a thorough grasp of how the system operates. Successful solutions and plans must take into consideration the present system’s reality.

This course delves into the foundations of the American healthcare system. It will present the major institutions and players in healthcare systems, explain what they do, and examine how they interact. The training will cover medical practices, hospitals, medicines, insurance, and finance. We will also talk about the problems of healthcare cost management, quality care, and access to treatment. While the course concentrates on the healthcare system in the United States, we will also discuss healthcare systems in other industrialized nations.

 

Course 2: Introduction to Clinical Data

• Rating: 4.6 stars

This course will teach you how to create a framework for successful and ethical medical data mining. We will investigate the various clinical data obtained throughout healthcare delivery. You will learn how to create datasets that are ready for analysis and how to use computational techniques to answer clinical issues. We will also look at concerns of justice and prejudice that may occur when we use healthcare information to make patient-care choices.

 

Course 3: Fundamentals of Machine Learning for Healthcare

• Rating: 4.8 stars

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Machine learning and artificial intelligence have the potential to change healthcare and offer up a world of limitless possibilities. Yet, we would never be able to realize these technologies’ full potential unless all stakeholders have a thorough knowledge of both healthcare and machine learning concepts and principles.

This course will cover the fundamental concepts and methods of machine learning as they relate to medicine and healthcare. We will look at machine learning techniques, medical use cases, healthcare-specific metrics, and best practices for developing, implementing, and assessing machine learning applications in healthcare. The course will provide non-engineering professionals in healthcare, health policy, pharmaceutical research, and data science with the skills to critically assess and apply these technologies. Geoffrey Angus is a co-author. Mars is one of the editors who contributed to this article.

 

Course 4: Evaluations of AI Applications in Healthcare

• Rating: 4.5 stars

With the proliferation of artificial intelligence applications all across the healthcare system, stakeholders are confronted with both the potential and problems of these developing technologies. This course delves into the concepts of AI deployment in healthcare as well as the framework used to assess the downstream implications of AI healthcare solutions.

 

Course 5: AI in Healthcare Capstone

• Rating: 4.6 stars

This capstone project leads you on an excursion of all the ideas we’ve studied so far in the various classes. We designed this interaction based on the experience of a patient who gets some respiratory symptoms and seeks treatment with a primary care physician due to worries about COVID19. We will track the patient’s journey via the lens of the data generated at each contact, leading us to a unique de-identified dataset developed just for this specialty. The data collection includes both EHR and imaging data, and we will use it to develop models that will allow us to make risk-stratification choices for our patients. We’ll go through how the various decisions you make, such as feature design, data types to utilize, how the model assessment is set up, and how you manage the patient chronology, impact the care that the model recommends. We will also explore the regulatory and ethical problems that arise when we seek to employ AI to assist us to make better care decisions for our patients during this investigation. This course will provide students with hands-on exposure to a medical data miner’s day.

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Conclusion

AI improves healthcare workers’ capacity to better comprehend the day-to-day patterns and requirements of the individuals they care for, allowing them to give greater feedback, advice, and support for remaining healthy. We hope that this review on AI Healthcare Specialization will help you understand if these courses are for you.

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