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Charles Ivan Niswander II
The medical imaging industry is set to see 9 and a half billion dollars in growth in just a few years, mostly due to advances in AI imaging technologies.
AI integration with medical imaging is expected to gain traction as it enables increased productivity, improved accuracy, and reduced errors in the diagnosis performed by technicians and radiologists. The use of AI will also automate the labor-intensive manual segmentation and enable technicians to identify abnormalities, in turn, accelerating the treatment process. Furthermore, AI platforms are also being developed for hospitals and health systems to help clinicians in making...
Read more
The medical imaging industry is set to see 9 and a half billion dollars in growth in just a few years, mostly due to advances in AI imaging technologies.
AI integration with medical imaging is expected to gain traction as it enables increased productivity, improved accuracy, and reduced errors in the diagnosis performed by technicians and radiologists. The use of AI will also automate the labor-intensive manual segmentation and enable technicians to identify abnormalities, in turn, accelerating the treatment process. Furthermore, AI platforms are also being developed for hospitals and health systems to help clinicians in making...
Read more
The medical imaging industry is set to see 9 and a half billion dollars in growth in just a few years, mostly due to advances in AI imaging technologies.
AI integration with medical imaging is expected to gain traction as it enables increased productivity, improved accuracy, and reduced errors in the diagnosis performed by technicians and radiologists. The use of AI will also automate the labor-intensive manual segmentation and enable technicians to identify abnormalities, in turn, accelerating the treatment process. Furthermore, AI platforms are also being developed for hospitals and health systems to help clinicians in making quick decisions and improving patient outcomes.
Ultimately, this field of research will benefit from more minds refining the technology. This project will get you started in using Python and Tensorflow/Keras for advanced medical imaging.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/gty8e8/medical
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches students how AI-enhanced medical imaging improves diagnostic accuracy, productivity, and reduces errors
Reinforces current industry trends in medical imaging advancements
Provides a foundation in using Python and TensorFlow/Keras for advanced medical imaging
Automates labor-intensive manual segmentation processes for technicians
Applicable to a variety of healthcare settings, including hospitals and health systems
Save this course
Save Medical Image Classification using Tensorflow to your list so you can find it easily later:
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Reviews summary
Limited practical usefulness
This course will let students work on projects to reinforce what they've learned in their machine learning studies. However, most students did not think that this course met expectations.
Course has a real-world use.
"This course is very useful for students who want to have some real projects to consolidate what they learned about machine learning."
Course includes hands-on experience.
"I've hands on experience with medical images for about 10 years and I've good knowledge on Python as well."
Files needed to complete the course were not provided.
"Bit frustrating to get to the end of a few hours worth of work and not have the code work (also I had to search for the image files on the internet, they were not provided nor was a link or anywhere to get them from)."
Code issues hinder learning.
"The entire project is typing the code without clear explanation of why we are doing it the way or why we are writing the code like that."
"There's some good concepts in here, but they're hardly explained. The code is now outdated, which is an avoidable issue, the requirements.txt file does not seem to rectify the issue either."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Medical Image Classification using Tensorflow with these
activities:
Review general concepts and terminology used in medical imaging
Show steps
Refresh your memory on the basic principles and concepts of medical imaging to ensure you have a strong foundation for the course materials
Browse courses on
Medical Imaging
Show steps
-
Review textbooks or online resources on medical imaging fundamentals
-
Complete practice problems or quizzes to test your understanding
Learn Python for Medical Imaging
Show steps
Follow a Python tutorial specifically designed for medical imaging to enhance your understanding of Python in this context.
Browse courses on
Python
Show steps
-
Identify a suitable tutorial.
-
Complete the tutorial.
Review Linear Algebra and Calculus
Show steps
Refresh your knowledge of linear algebra and calculus to strengthen your mathematical foundation for AI imaging.
Browse courses on
Linear Algebra
Show steps
-
Review concepts such as matrices, vectors, and linear transformations.
-
Practice solving calculus problems involving derivatives and integrals.
-
Apply your refreshed knowledge to understand AI imaging algorithms.
21 other activities
Expand to see all activities and additional details
Show all 24 activities
Refresher course on Python
Show steps
This activity will provide a solid foundation for students to build upon throughout the course.
Browse courses on
Python Programming
Show steps
-
Review the basics of Python syntax.
-
Complete practice exercises on data types, variables, and operators.
-
Create a small Python program that demonstrates your understanding of loops and conditional statements.
Review Python basics
Show steps
Brush up on Python programming to refresh your memory and prepare for this course.
Browse courses on
Python
Show steps
-
Review Python syntax and data structures.
-
Practice writing simple Python programs.
-
Complete a few Python tutorials or exercises.
Volunteer at a medical imaging facility
Show steps
This activity will give students the opportunity to see how AI is used in a clinical setting and to make connections with professionals in the field.
Browse courses on
Medical Imaging
Show steps
-
Contact a local medical imaging facility and inquire about volunteer opportunities.
-
Complete any necessary training or background checks.
-
Volunteer regularly and assist with tasks such as patient care, data entry, or research.
Attend webinars or conferences on medical imaging
Show steps
Connect with experts and learn about the latest advancements in medical imaging and AI by attending webinars or conferences.
Browse courses on
Medical Imaging
Show steps
-
Search for upcoming webinars or conferences on medical imaging.
-
Register for the events that interest you.
-
Attend the events and actively participate in discussions.
Join a Medical Imaging AI Study Group
Show steps
Participate in peer study groups to discuss concepts, share knowledge, and collaborate on projects related to medical imaging AI.
Show steps
-
Find or create a study group with other students interested in medical imaging AI.
-
Meet regularly to discuss course material, share resources, and work on projects together.
-
Provide feedback and support to your peers.
Follow TensorFlow tutorials
Show steps
Reinforce your understanding of TensorFlow by following guided tutorials and hands-on exercises.
Browse courses on
TensorFlow
Show steps
-
Find a comprehensive TensorFlow tutorial series.
-
Follow the tutorials step-by-step, completing all exercises.
-
Experiment with the TensorFlow API on your own.
Form a Study Group
Show steps
Join or create a study group with other students taking this course to enhance your understanding through collaboration and discussion.
Show steps
-
Reach out to other students in the course.
-
Meet regularly to discuss the course material.
Follow tutorials on using Python and TensorFlow/Keras for medical imaging
Show steps
Develop proficiency in the programming tools and techniques used in the course by following guided tutorials and practicing hands-on
Browse courses on
Python
Show steps
-
Find tutorials or online courses on Python and TensorFlow/Keras for medical imaging
-
Complete the tutorials and practice exercises
-
Build a small project using the techniques learned
Follow TensorFlow Tutorials for Medical Imaging
Show steps
Complement your learning by following guided tutorials from TensorFlow to gain practical experience in medical imaging AI.
Show steps
-
Identify relevant TensorFlow tutorials for medical imaging.
-
Follow the tutorials step-by-step and implement the techniques.
-
Experiment with different parameters and settings to optimize your results.
TensorFlow/Keras tutorials
Show steps
This activity will provide students with hands-on experience using the tools they will need for the course.
Browse courses on
TensorFlow
Show steps
-
Follow a TensorFlow/Keras tutorial on building a simple neural network.
-
Experiment with different hyperparameters to improve the performance of your neural network.
-
Apply your knowledge to a real-world dataset.
Solve coding challenges
Show steps
Test your skills and identify areas for improvement by solving coding challenges related to medical imaging.
Browse courses on
Coding
Show steps
-
Find a website or platform that offers medical imaging coding challenges.
-
Attempt to solve the challenges on your own.
-
Review solutions and discuss your approach with others.
-
Identify areas where you need additional practice and focus your efforts accordingly.
TensorFlow Intro Tutorial
Show steps
Complete the TensorFlow intro tutorial to review and reinforce your understanding of the TensorFlow library.
Browse courses on
TensorFlow
Show steps
-
Go to the TensorFlow website and follow the tutorial.
Deep Learning for Medical Image Analysis
Show steps
This book provides a comprehensive overview of deep learning techniques for medical image analysis, which will supplement the course content.
View
Deep Network Design for Medical Image Computing...
on Amazon
Show steps
-
Read the book and take notes.
-
Complete the practice exercises in the book.
-
Apply the concepts from the book to your own projects.
Participate in online forums or discussion groups related to medical imaging
Show steps
Engage with other learners and professionals in the field to discuss concepts, share knowledge, and clarify doubts
Browse courses on
Medical Imaging
Show steps
-
Join online forums or discussion groups dedicated to medical imaging
-
Actively participate in discussions, ask questions, and share your insights
-
Help other learners by answering their questions and providing guidance
Complete coding drills and exercises on medical imaging data
Show steps
Sharpen your coding skills and apply your knowledge of Python and TensorFlow/Keras to real-world medical imaging data
Browse courses on
Medical Imaging
Show steps
-
Find online coding platforms or resources with medical imaging datasets
-
Solve coding challenges or complete exercises using the datasets
-
Review your solutions and identify areas for improvement
Create A Medical Imaging AI Project
Show steps
Build your own AI imaging project to solidify your understanding of the concepts covered in this course.
Show steps
-
Define your project scope and goals.
-
Gather and prepare your data.
-
Build your AI model using TensorFlow or Keras.
-
Evaluate and improve your model's performance.
-
Present your project findings.
Create a medical imaging project
Show steps
Apply your knowledge by creating a project that demonstrates your understanding of medical imaging and AI techniques.
Browse courses on
Medical Imaging
Show steps
-
Identify a problem or area of interest in medical imaging.
-
Develop a plan for your project, including the goals, methods, and expected outcomes.
-
Collect and prepare the necessary data.
-
Implement your project using Python and Tensorflow/Keras.
-
Evaluate the results of your project.
Practice medical image analysis tasks
Show steps
This activity will help students develop the skills necessary to complete the course assignments and projects.
Browse courses on
Medical Image Analysis
Show steps
-
Segment medical images using a provided segmentation tool.
-
Classify medical images using a pre-trained model.
-
Develop a custom model for medical image analysis.
Create a blog post or article on AI in medical imaging
Show steps
This activity will allow students to synthesize their understanding of the course material and share their knowledge with others.
Browse courses on
Medical Image Analysis
Show steps
-
Research the current state of AI in medical imaging.
-
Identify the challenges and opportunities of using AI in medical imaging.
-
Write a blog post or article that shares your insights.
Kaggle medical imaging competition
Show steps
This activity will provide students with an opportunity to apply their skills to a real-world problem and compete with other students around the world.
Browse courses on
Kaggle Competitions
Show steps
-
Join a Kaggle medical imaging competition.
-
Develop a model to solve the competition's problem.
-
Submit your model and track your progress.
Build a medical image analysis application
Show steps
This activity will challenge students to apply the skills they have learned in the course to create a complete medical image analysis application.
Show steps
-
Identify a medical imaging problem that you want to solve.
-
Collect a dataset of medical images.
-
Develop a deep learning model for your application.
-
Design and implement a user interface for your application.
-
Deploy your application to a cloud platform.
Review general concepts and terminology used in medical imaging
Show steps
Refresh your memory on the basic principles and concepts of medical imaging to ensure you have a strong foundation for the course materials
Browse courses on
Medical Imaging
Show steps
Show steps
Show steps
- Review textbooks or online resources on medical imaging fundamentals
- Complete practice problems or quizzes to test your understanding
Learn Python for Medical Imaging
Show steps
Follow a Python tutorial specifically designed for medical imaging to enhance your understanding of Python in this context.
Browse courses on
Python
Show steps
Show steps
Show steps
- Identify a suitable tutorial.
- Complete the tutorial.
Review Linear Algebra and Calculus
Show steps
Refresh your knowledge of linear algebra and calculus to strengthen your mathematical foundation for AI imaging.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review concepts such as matrices, vectors, and linear transformations.
- Practice solving calculus problems involving derivatives and integrals.
- Apply your refreshed knowledge to understand AI imaging algorithms.
21 other activities
Expand to see all activities and additional details
Show all 24 activities
Refresher course on Python
Show steps
This activity will provide a solid foundation for students to build upon throughout the course.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review the basics of Python syntax.
- Complete practice exercises on data types, variables, and operators.
- Create a small Python program that demonstrates your understanding of loops and conditional statements.
Review Python basics
Show steps
Brush up on Python programming to refresh your memory and prepare for this course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review Python syntax and data structures.
- Practice writing simple Python programs.
- Complete a few Python tutorials or exercises.
Volunteer at a medical imaging facility
Show steps
This activity will give students the opportunity to see how AI is used in a clinical setting and to make connections with professionals in the field.
Browse courses on
Medical Imaging
Show steps
Show steps
Show steps
- Contact a local medical imaging facility and inquire about volunteer opportunities.
- Complete any necessary training or background checks.
- Volunteer regularly and assist with tasks such as patient care, data entry, or research.
Attend webinars or conferences on medical imaging
Show steps
Connect with experts and learn about the latest advancements in medical imaging and AI by attending webinars or conferences.
Browse courses on
Medical Imaging
Show steps
Show steps
Show steps
- Search for upcoming webinars or conferences on medical imaging.
- Register for the events that interest you.
- Attend the events and actively participate in discussions.
Join a Medical Imaging AI Study Group
Show steps
Participate in peer study groups to discuss concepts, share knowledge, and collaborate on projects related to medical imaging AI.
Show steps
Show steps
Show steps
- Find or create a study group with other students interested in medical imaging AI.
- Meet regularly to discuss course material, share resources, and work on projects together.
- Provide feedback and support to your peers.
Follow TensorFlow tutorials
Show steps
Reinforce your understanding of TensorFlow by following guided tutorials and hands-on exercises.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Find a comprehensive TensorFlow tutorial series.
- Follow the tutorials step-by-step, completing all exercises.
- Experiment with the TensorFlow API on your own.
Form a Study Group
Show steps
Join or create a study group with other students taking this course to enhance your understanding through collaboration and discussion.
Show steps
Show steps
Show steps
- Reach out to other students in the course.
- Meet regularly to discuss the course material.
Follow tutorials on using Python and TensorFlow/Keras for medical imaging
Show steps
Develop proficiency in the programming tools and techniques used in the course by following guided tutorials and practicing hands-on
Browse courses on
Python
Show steps
Show steps
Show steps
- Find tutorials or online courses on Python and TensorFlow/Keras for medical imaging
- Complete the tutorials and practice exercises
- Build a small project using the techniques learned
Follow TensorFlow Tutorials for Medical Imaging
Show steps
Complement your learning by following guided tutorials from TensorFlow to gain practical experience in medical imaging AI.
Show steps
Show steps
Show steps
- Identify relevant TensorFlow tutorials for medical imaging.
- Follow the tutorials step-by-step and implement the techniques.
- Experiment with different parameters and settings to optimize your results.
TensorFlow/Keras tutorials
Show steps
This activity will provide students with hands-on experience using the tools they will need for the course.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Follow a TensorFlow/Keras tutorial on building a simple neural network.
- Experiment with different hyperparameters to improve the performance of your neural network.
- Apply your knowledge to a real-world dataset.
Solve coding challenges
Show steps
Test your skills and identify areas for improvement by solving coding challenges related to medical imaging.
Browse courses on
Coding
Show steps
Show steps
Show steps
- Find a website or platform that offers medical imaging coding challenges.
- Attempt to solve the challenges on your own.
- Review solutions and discuss your approach with others.
- Identify areas where you need additional practice and focus your efforts accordingly.
TensorFlow Intro Tutorial
Show steps
Complete the TensorFlow intro tutorial to review and reinforce your understanding of the TensorFlow library.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Go to the TensorFlow website and follow the tutorial.
Deep Learning for Medical Image Analysis
Show steps
This book provides a comprehensive overview of deep learning techniques for medical image analysis, which will supplement the course content.
View
Deep Network Design for Medical Image Computing...
on Amazon
Show steps
Show steps
Show steps
- Read the book and take notes.
- Complete the practice exercises in the book.
- Apply the concepts from the book to your own projects.
Participate in online forums or discussion groups related to medical imaging
Show steps
Engage with other learners and professionals in the field to discuss concepts, share knowledge, and clarify doubts
Browse courses on
Medical Imaging
Show steps
Show steps
Show steps
- Join online forums or discussion groups dedicated to medical imaging
- Actively participate in discussions, ask questions, and share your insights
- Help other learners by answering their questions and providing guidance
Complete coding drills and exercises on medical imaging data
Show steps
Sharpen your coding skills and apply your knowledge of Python and TensorFlow/Keras to real-world medical imaging data
Browse courses on
Medical Imaging
Show steps
Show steps
Show steps
- Find online coding platforms or resources with medical imaging datasets
- Solve coding challenges or complete exercises using the datasets
- Review your solutions and identify areas for improvement
Create A Medical Imaging AI Project
Show steps
Build your own AI imaging project to solidify your understanding of the concepts covered in this course.
Show steps
Show steps
Show steps
- Define your project scope and goals.
- Gather and prepare your data.
- Build your AI model using TensorFlow or Keras.
- Evaluate and improve your model's performance.
- Present your project findings.
Create a medical imaging project
Show steps
Apply your knowledge by creating a project that demonstrates your understanding of medical imaging and AI techniques.
Browse courses on
Medical Imaging
Show steps
Show steps
Show steps
- Identify a problem or area of interest in medical imaging.
- Develop a plan for your project, including the goals, methods, and expected outcomes.
- Collect and prepare the necessary data.
- Implement your project using Python and Tensorflow/Keras.
- Evaluate the results of your project.
Practice medical image analysis tasks
Show steps
This activity will help students develop the skills necessary to complete the course assignments and projects.
Browse courses on
Medical Image Analysis
Show steps
Show steps
Show steps
- Segment medical images using a provided segmentation tool.
- Classify medical images using a pre-trained model.
- Develop a custom model for medical image analysis.
Create a blog post or article on AI in medical imaging
Show steps
This activity will allow students to synthesize their understanding of the course material and share their knowledge with others.
Browse courses on
Medical Image Analysis
Show steps
Show steps
Show steps
- Research the current state of AI in medical imaging.
- Identify the challenges and opportunities of using AI in medical imaging.
- Write a blog post or article that shares your insights.
Kaggle medical imaging competition
Show steps
This activity will provide students with an opportunity to apply their skills to a real-world problem and compete with other students around the world.
Browse courses on
Kaggle Competitions
Show steps
Show steps
Show steps
- Join a Kaggle medical imaging competition.
- Develop a model to solve the competition's problem.
- Submit your model and track your progress.
Build a medical image analysis application
Show steps
This activity will challenge students to apply the skills they have learned in the course to create a complete medical image analysis application.
Show steps
Show steps
Show steps
- Identify a medical imaging problem that you want to solve.
- Collect a dataset of medical images.
- Develop a deep learning model for your application.
- Design and implement a user interface for your application.
- Deploy your application to a cloud platform.
Career center
Learners who complete Medical Image Classification using Tensorflow will develop knowledge and skills
that may be useful to these careers:
Healthcare Data Analyst
Healthcare Data Analyst
Healthcare Data Analysts use their knowledge of data analysis and statistics to improve the quality and efficiency of healthcare. They work with healthcare providers, insurers, and other stakeholders to collect, analyze, and interpret data to identify trends and patterns. This course may be useful for Healthcare Data Analysts who want to learn more about AI and machine learning techniques for medical imaging.
Radiation Therapist
Radiation Therapist
Radiation Therapists use radiation to treat cancer and other diseases. They work with oncologists and other medical professionals to develop and implement radiation therapy plans. This course may be useful for Radiation Therapists who want to learn more about AI and machine learning techniques for medical imaging.
Medical Physicist
Medical Physicist
Medical Physicists use their knowledge of physics to develop and improve medical imaging systems and techniques. They work with radiologists and other medical professionals to ensure that medical imaging systems are safe, accurate, and efficient. This course may be useful for Medical Physicists who want to learn more about AI and machine learning techniques for medical imaging.
Radiologist
Radiologist
Radiologists use medical imaging technologies to diagnose and treat diseases. They interpret medical images, such as X-rays, CT scans, and MRIs, to identify abnormalities and make diagnoses. This course may be useful for Radiologists who want to learn more about AI and machine learning techniques for medical imaging.
Nuclear Medicine Technologist
Nuclear Medicine Technologist
Nuclear Medicine Technologists use radioactive isotopes to diagnose and treat diseases. They work with nuclear medicine physicians and other medical professionals to develop and implement nuclear medicine procedures. This course may be useful for Nuclear Medicine Technologists who want to learn more about AI and machine learning techniques for medical imaging.
Medical Dosimetrist
Medical Dosimetrist
Medical Dosimetrists use their knowledge of radiation physics to calculate the amount of radiation that is delivered to patients during radiation therapy. They work with Radiation Therapists and other medical professionals to develop and implement radiation therapy plans. This course may be useful for Medical Dosimetrists who want to learn more about AI and machine learning techniques for medical imaging.
Medical Imaging Technologist
Medical Imaging Technologist
Medical Imaging Technologists operate medical imaging equipment, such as X-ray machines, CT scanners, and MRIs. They work with radiologists and other medical professionals to ensure that medical imaging systems are safe, accurate, and efficient. This course may be useful for Medical Imaging Technologists who want to learn more about AI and machine learning techniques for medical imaging.
Ultrasound Technologist
Ultrasound Technologist
Ultrasound Technologists use ultrasound waves to diagnose and treat diseases. They work with obstetricians, gynecologists, and other medical professionals to develop and implement ultrasound procedures. This course may be useful for Ultrasound Technologists who want to learn more about AI and machine learning techniques for medical imaging.
Healthcare Informatics Specialist
Healthcare Informatics Specialist
Healthcare Informatics Specialists use their knowledge of information technology and healthcare to develop and implement healthcare information systems. They work with healthcare providers, insurers, and other stakeholders to design, implement, and maintain healthcare information systems. This course may be useful for Healthcare Informatics Specialists who want to learn more about AI and machine learning techniques for medical imaging.
Radiographer
Radiographer
Radiographers use X-rays to diagnose and treat diseases. They work with radiologists and other medical professionals to develop and implement X-ray procedures. This course may be useful for Radiographers who want to learn more about AI and machine learning techniques for medical imaging.
Magnetic Resonance Imaging Technologist
Magnetic Resonance Imaging Technologist
Magnetic Resonance Imaging Technologists use magnetic resonance imaging (MRI) machines to diagnose and treat diseases. They work with radiologists and other medical professionals to develop and implement MRI procedures. This course may be useful for Magnetic Resonance Imaging Technologists who want to learn more about AI and machine learning techniques for medical imaging.
Medical Imaging Scientist
Medical Imaging Scientist
Medical Imaging Scientists use their knowledge of medical imaging technologies to develop and improve medical imaging systems and techniques. They work with radiologists and other medical professionals to ensure that medical imaging systems are safe, accurate, and efficient. This course may be useful for Medical Imaging Scientists who want to learn more about AI and machine learning techniques for medical imaging.
Computed Tomography Technologist
Computed Tomography Technologist
Computed Tomography Technologists use computed tomography (CT) machines to diagnose and treat diseases. They work with radiologists and other medical professionals to develop and implement CT procedures. This course may be useful for Computed Tomography Technologists who want to learn more about AI and machine learning techniques for medical imaging.
Positron Emission Tomography Technologist
Positron Emission Tomography Technologist
Positron Emission Tomography Technologists use positron emission tomography (PET) machines to diagnose and treat diseases. They work with nuclear medicine physicians and other medical professionals to develop and implement PET procedures. This course may be useful for Positron Emission Tomography Technologists who want to learn more about AI and machine learning techniques for medical imaging.
Radiation Therapist Assistant
Radiation Therapist Assistant
Radiation Therapist Assistants work with Radiation Therapists to deliver radiation therapy to patients. They help patients prepare for and undergo radiation therapy, and they monitor patients during and after treatment. This course may be useful for Radiation Therapist Assistants who want to learn more about AI and machine learning techniques for medical imaging.
For more career information including salaries, visit:
OpenCourser.com/course/gty8e8/medical
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Medical Image Classification using Tensorflow .
Provides a comprehensive guide to using Python for deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a practical guide to using Python for machine learning. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning.
Provides a practical guide to using Scikit-Learn, Keras, and TensorFlow for machine learning. It covers topics such as data preprocessing, feature engineering, and model training.
Provides a practical guide to using fastai and PyTorch for deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of deep learning techniques for natural language processing. It covers topics such as text classification, sentiment analysis, and machine translation.
Provides a comprehensive overview of speech and language processing. It covers topics such as speech recognition, language modeling, and natural language understanding.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/gty8e8/medical
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Charles Ivan Niswander II
Good to know
Teaches students how AI-enhanced medical imaging improves diagnostic accuracy, productivity, and reduces errors
Reinforces current industry trends in medical imaging advancements
Provides a foundation in using Python and TensorFlow/Keras for advanced medical imaging
Automates labor-intensive manual segmentation processes for technicians
Applicable to a variety of healthcare settings, including hospitals and health systems
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