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Aster Health Academy > Technology > Artificial Intelligence in Healthcare: Theory to Practice

Artificial Intelligence in Healthcare: Theory to Practice

Video Lectures, virtual connect sessions on weekends
Market case studies, Comprehensive Healthcare Cases
Conversations with industry experts and capstone Project

Course Outcomes:

  • Tailored experiential (practical oriented) curriculum designed for healthcare professionals
  • More than 50% curriculum dedicated to the practical application of artificial intelligence in solving healthcare challenges
  • Live weekend sessions by top Artificial Intelligence faculty of Indian Institute of Science
  • Dedicated mentorship by Artificial Intelligence expert faculty
  • Exclusive mathematics/computing bridge module designed for healthcare professionals
  • Certificate from Indian Institute of Science and Aster Health Academy

About the course:

This comprehensive program is designed to equip healthcare professionals with the knowledge and skills required to harness the power of Artificial Intelligence (AI) in the field of healthcare. Throughout this program, you will delve into the theoretical as well as practical aspects of Artificial Intelligence in solving complex healthcare problems. By the end of this program, you will not only understand the fundamental principles of Artificial Intelligence but also be adept at applying AI methods to address real-world healthcare challenges.

This all-inclusive program is thought by expert Artificial Intelligence faculty members of the Indian Institute of Science (IISc) and will also have an exclusive Mathematics/Computing bridge module designed for healthcare professionals, ensuring you have the essential foundation required to excel in this program. Get ready to embark on an exciting journey, led by the esteemed faculty of IISc, that bridges the gap between theory and practice, empowering you to make a significant impact in the dynamic realm of Artificial Intelligence-driven healthcare.

Curriculum:


Module 1: AI in Healthcare: Preliminaries/Basics (Total: 12 Hours)

1
Introduction to: (a) Python and (c) Pytorch/Tensorflow.
2
Basic Mathematics (Linear Algebra, Probability, and Optimization)
3
Basics of Digital Data; Health Records
4
Number Representation in computer: Precision/Floating Point Operations
5
Signal/Speech/Image as data: Digitization, quantization
6
Computing Platforms: GPU Vs CPU
7
Programming Exercises: Tensorflow/Pytorch (one-on-one sessions)

Module 2: AI in Healthcare: Theory (Total: 14 Hours)

1
Healthcare: Digital Journey, Sources of Data, Need for Artificial Intelligence
2
Information Systems in Healthcare: DICOM/HL7-IHE
3
Overview of biological and medical imaging modalities and research/clinical applications
4
Challenges in healthcare data handling and curation
5
Medical imaging tools (viewers, formats, etc.)
6
Medical Image Segmentation: Challenges/Basic Methods/Metrics of Evaluation
7
Physiological signal processing: Speech/ECG/EEG
8
Machine Learning Methods: Linear Regression, Logistic Regression, Clustering
9
Introduction to Neural networks and Deep Learning

Feedforward NN, Principles of training, CNNs, Loss Functions, etc. 

10
Introduction to Natural Language Processing

Tasks, Representation Learning, Word2Vec, Knowledge Graphs

Module 3: AI in Healthcare: Practice* (Total: 24 Hours)

1
Chest X-Ray Image Analysis: Classification/Detection
2
Fundus Image Analysis for Retinal Disease Detection
3
Lung Ultrasound Image Analysis
4
ECG Signal Analysis
5
Brain Tumor Detection
6
Median Nerve Segmentation in Nerve Ultrasound Images

Who this course is for:

This course is tailored for healthcare professionals, data scientists, researchers, academics, health IT professionals, policy makers, administrators, and aspiring entrepreneurs who are passionate about leveraging Artificial Intelligence to transform healthcare. This comprehensive program equips participants with the knowledge and skills to apply Artificial Intelligence techniques in areas such as diagnostics, treatment planning, predictive modeling, medical research, and health informatics. Whether you are seeking to enhance patient care, drive innovation, or navigate the ethical and regulatory aspects of Artificial Intelligence in healthcare, this course provides a valuable platform for individuals from diverse backgrounds to explore and excel at the intersection of Artificial Intelligence and healthcare.

Knowledge Partner:

The Indian Institute of Science (IISc) is our knowledge partner for the Artificial Intelligence in Healthcare: Theory to Practice course. As a prestigious institution renowned for its academic excellence and ground-breaking research, IISc brings unparalleled expertise and resources to our program. Collaborating with IISc ensures that our course benefits from their vast knowledge in areas such as Artificial Intelligence, healthcare, and interdisciplinary studies. Through this partnership, we are able to provide learners with a unique opportunity to learn from distinguished faculty members, access cutting-edge facilities, and engage in innovative research at the forefront of Artificial Intelligence in healthcare. This collaboration with IISc reinforces our commitment to delivering a top-tier educational experience and advancing the field of Artificial Intelligence in healthcare.

Sample Certificate:

FAQ:

The course duration will be 12 weeks.
You will be granted full access to the learning content for 36 months, starting from the date of enrollment.
The time investment for the course includes 4-6 hours per week for asynchronous learning and 3 hours of synchronous sessions on Sunday mornings, along with post-lunch doubt clearing sessions conducted by teaching assistants.
The weekend synchronous sessions, conducted by esteemed faculty from the Indian Institute of Science (IISc), are scheduled for approximately 3 hours. Most sessions are held on Sunday mornings, with additional time allocated for doubt clearing sessions in the post lunch hours.
Yes. After successful completion of the course, you will be awarded a certificate from both Indian Institute of Science (IISc) and Aster Heath Academy.
Yes, we offer financial aid opportunities for participants.
Here's the structure of our refund policy: 1) A candidate is eligible for 75% refund if the drop out is within 7 days of launch of the program 2) A candidate is eligible for 50% refund if the drop out is within 8- 15 days of launch of the program 3) There is no refund if the drop out is after 15 days of launch

Faculty Team

Prof. Phaneendra Yalavarthy
Professor
Department of Computational and Data Sciences, IISc, Bangalore, India
Prof. Yalavarthy is a renowned artificial intelligence expert in the area of medical imaging. He has published more than 70 international journal articles in the area of medical imaging and leads successful collaborative labs with industries like GE Healthcare. He was instrumental in establishing Aster AI Lab, which is one of the first AI labs in India in a healthcare facility. He has active engagements with the medical imaging industry stake holders including GE Healthcare, Siemens Healthiness, Samsung Healthcare, and Teleradiology Solutions, fostering impactful collaborations. His research interests include artificial intelligence in medical imaging, digital health, and biomedical signal processing.
Dr. Lokesh B
Neurologist
Aster CMI Hospital, Bangalore
Dr. Lokesh is the head of Neurosciences at Aster CMI Hospital, has trained in cerebrovascular Sonography from National University Hospital, Singapore and the University of Alabama, Birmingham, USA. He has also trained in peripheral nerve and muscle sonography from the Institute of Neurology, Italy & Netherlands. He leads the Aster AI lab and collaborates actively with Indian Institute of Science. He is passionate about application of artificial intelligence in healthcare and improving the patient care. He completed MBBS, MD in General medicine and DM Neurology from Kasturba medical college, Manipal, India.
Prof. Ambedkar Dukkipati
Professor of Artificial Intelligence
Computer Science and Automation, IISc, Bangalore, India
Prof. Dukkipati is an expert faculty member of artificial intelligence at IISc and teaches machine learning/deep learning courses regularly. He leads Statistics and Machine Learning group at IISc. He has active collaborations with GE Healthcare, Novartis, and Shell Technology Centre in the area of artificial intelligence. His research interests include machine learning, network representation learning, sequential decision-making under uncertainty, and deep reinforcement learning.
Prof. Chandrasekhar Seelamantula
Professor of Signal Processing
Electrical Engineering, IISc, Bangalore India
Prof. Seelamantula is a renowned expert in the biomedical signal processing at IISc. He teaches neural signal processing, digital signal processing, and digital image processing regularly at IISc. He has active collaborations with Carl Zeiss Research, Tech Mahindra, and Qualcomm in the area of artificial intelligence. His research areas include speech, biomedical, and image processing, computational imaging, and AI for digital healthcare.
Dr. Vaanathi Sundaresan
Assistant Professor of Department of Computational and Data Sciences (CDS) , IISc, Bangalore
Dr. Vaanathi Sundaresan is an assistant professor at IISc, where she leads the Biomedical Image Analysis (BioMedIA) laboratory. Her academic journey includes postdoctoral work at Harvard Medical School, a doctorate from the University of Oxford, and an M.S. from IITM. She specializes in diverse research areas, including machine learning, medical imaging, neuroimaging, and tool development.

Curriculum:


Module 1: AI in Healthcare: Preliminaries/Basics (Total: 12 Hours)

1
Introduction to: (a) Python and (c) Pytorch/Tensorflow.
2
Basic Mathematics (Linear Algebra, Probability, and Optimization)
3
Basics of Digital Data; Health Records
4
Number Representation in computer: Precision/Floating Point Operations
5
Signal/Speech/Image as data: Digitization, quantization
6
Computing Platforms: GPU Vs CPU
7
Programming Exercises: Tensorflow/Pytorch (one-on-one sessions)

Module 2: AI in Healthcare: Theory (Total: 14 Hours)

1
Healthcare: Digital Journey, Sources of Data, Need for Artificial Intelligence
2
Information Systems in Healthcare: DICOM/HL7-IHE
3
Overview of biological and medical imaging modalities and research/clinical applications
4
Challenges in healthcare data handling and curation
5
Medical imaging tools (viewers, formats, etc.)
6
Medical Image Segmentation: Challenges/Basic Methods/Metrics of Evaluation
7
Physiological signal processing: Speech/ECG/EEG
8
Machine Learning Methods: Linear Regression, Logistic Regression, Clustering
9
Introduction to Neural networks and Deep Learning

Feedforward NN, Principles of training, CNNs, Loss Functions, etc. 

10
Introduction to Natural Language Processing

Tasks, Representation Learning, Word2Vec, Knowledge Graphs

Module 3: AI in Healthcare: Practice* (Total: 24 Hours)

1
Chest X-Ray Image Analysis: Classification/Detection
2
Fundus Image Analysis for Retinal Disease Detection
3
Lung Ultrasound Image Analysis
4
ECG Signal Analysis
5
Brain Tumor Detection
6
Median Nerve Segmentation in Nerve Ultrasound Images

FAQ:

The course duration will be 12 weeks.
You will be granted full access to the learning content for 36 months, starting from the date of enrollment.
The time investment for the course includes 4-6 hours per week for asynchronous learning and 3 hours of synchronous sessions on Sunday mornings, along with post-lunch doubt clearing sessions conducted by teaching assistants.
The weekend synchronous sessions, conducted by esteemed faculty from the Indian Institute of Science (IISc), are scheduled for approximately 3 hours. Most sessions are held on Sunday mornings, with additional time allocated for doubt clearing sessions in the post lunch hours.
Yes. After successful completion of the course, you will be awarded a certificate from both Indian Institute of Science (IISc) and Aster Heath Academy.
Yes, we offer financial aid opportunities for participants.
Here's the structure of our refund policy: 1) A candidate is eligible for 75% refund if the drop out is within 7 days of launch of the program 2) A candidate is eligible for 50% refund if the drop out is within 8- 15 days of launch of the program 3) There is no refund if the drop out is after 15 days of launch

Duration: 3 Months

Level: advanced

Price:
Buy Now

Batch Start Date

30th Sep, 2024

Next Application Review Date

07th Mar, 2024

Application Form








    Includes

    Full lifetime access
    Access on mobile and TV
    Artificial Intelligence in Healthcare: Theory to Practice
    Price:
    INR 125,000*
    GST as applicable

    Buy Now
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