Artificial Intelligence in Healthcare: Theory to Practice
Integrate AI in healthcare for a smarter future
Course Outcomes:
About the course:
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:
Knowledge Partner:
Sample Certificate:
FAQ:
Faculty Team
Prof. Phaneendra Yalavarthy
Professor
Department of Computational and Data Sciences, IISc, Bangalore, India
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 Healthineers, 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
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
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.
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:
Duration: 3 Months
Level: advanced
Batch Start Date
24th Aug, 2024Next Application Review Date
24th Aug, 2024Application Form
Includes
Full lifetime access
Access on mobile and TV
Artificial Intelligence in Healthcare: Theory to Practice
Price:
INR 125,000*
GST as applicable
