Globally innovation in artificial intelligence (AI) will reshape healthcare systems. However, like all innovation not all technologies will realize the value that innovators claim, nor the efficiencies imagined. Many, will not be implementable across or within our internationally diverse healthcare systems. To support innovation, the UK has established the Accelerated Access Collaborative; to identify and accelerate those innovations which have the potential to be of real value to the UK NHS.
Within India, AI-enabled healthcare, like the automated analysis of medical tests, diagnosis prediction, automation of healthcare diagnosis, and wearable sensor-based medical devices, are expected to revolutionize treatment. Government initiatives, such as The Information Technology Act, 2000 and the National e Health Authority, aim to improve the access, and implementation of AI. The use and applications of AI solutions has the potential to help improve access to, and delivery of health care across the country. This is vital as India has one of the lowest patient-doctor ratios in the world (1700:1). Whilst 70% of the country’s population live in rural areas, 70% of the healthcare infrastructure is in cities (70-70 paradox).
Most AI applications in development are driven by innovators, most often engineers, often focused on what is technically feasible; not what is practical or needed. There a need to close this gap. Further, AI innovations need robust evaluation to Globally innovation in artificial intelligence (AI) will reshape healthcare systems. However, like all innovation not all technologies will realize the value that innovators claim, nor the efficiencies imagined. Many, will not be implementable across or within our internationally diverse healthcare systems. To support innovation, the UK has established the Accelerated Access Collaborative; to identify and accelerate those innovations which have the potential to be of real value to the UK NHS.
Within India, AI-enabled healthcare, like the automated analysis of medical tests, diagnosis prediction, automation of healthcare diagnosis, and wearable sensor-based medical devices, are expected to revolutionize treatment. Government initiatives, such as The Information Technology Act, 2000 and the National e Health Authority, aim to improve the access, and implementation of AI. The use and applications of AI solutions has the potential to help improve access to, and delivery of health care across the country. This is vital as India has one of the lowest patient-doctor ratios in the world (1700:1). Whilst 70% of the country’s population live in rural areas, 70% of the healthcare infrastructure is in cities (70-70 paradox).
Most AI applications in development are driven by innovators, most often engineers, often focused on what is technically feasible; not what is practical or needed. There a need to close this gap. Further, AI innovations need robust evaluation to ensure that implementation is supported by sufficient effectiveness evidence and via the regulatory systems/government bodies. Enabling this innovation pathway will support the widespread, appropriate, adoption of AI, such as machine learning, digital interventions and data science tools in clinical and public health that serve the public and relieve the burden on health-care systems.
Benefits: This workshop will enable early career researchers to acquire the knowledge and skills needed to understand applications of AI and ML in clinical and public health. It will enable researchers to establish networks within academia, industry, and government; vital if successful collaborative research studies in AI and ML that address real clinical and public health needs and can make real differences in reducing the inequalities in health those less well off in society face are to be developed.
Day 1 – January 14, 2022 | |||
Timing | Topic | India Faculty | UK Faculty |
9.30 – 11.00 | Artificial Intelligence and Machine Learning: Big picture | Lead | Contributor |
Presentation on AI/ML field and initial reflections in health applications | Lead | Contributor | |
11.30 – 12.30 | Strategies to enhance data integration ton advance AI/ML | Lead | Contributor |
Role of data integration and sharing in enhancing AI & ML algorithms to improve health and healthcare | Lead | Contributor | |
1.30 – 3.00 | AI/ML opportunities in health and healthcare | Lead | Contributor |
Areas where AI/ML has the potential to improve in health and healthcare | Lead | Contributor | |
3.30 – 5:00 | Addressing challenges of AI/ML implementation & integration | Lead | Contributor |
Focus on integration and intrinsic reliability challenges; human upskilling | Lead | Contributor |
Day 2 – January 15, 2022 | |||
Timing | Topic | India Faculty | UK Faculty |
9.30 – 11.00 | Technical validation studies of AI/ML in clinical practice and public health | Lead | Contributor |
Algorithm robustness, reproducibility, generalizability | Lead | Contributor | |
11.30 – 12.30 | Integrating AI/ML in clinical guidelines and public health care pathways | Co-Lead | Co-Lead |
1.30 – 3.00 | Case studies from UK and India | UK-Lead | India- Lead (Dr. Santosh) |
3.30 – 5:00 | Participant presentations on case studies of AI/ML applications in health and healthcare in UK and India | Co-Lead | Co-Lead |
Day 3 – January 16, 2022 | |||
Timing | Topic | India Faculty | UK Faculty |
9.30 – 11.00 | Transferability of standard clinical and public health evaluations to AI/ML applications in health and healthcare | Contributor | Lead |
11.30 – 12.30 | RCTs and Observational studies of AI/ML in health and healthcare | Lead | Lead |
Use of experimental and non-experimental studies in AI/ML evaluations | Lead | Lead | |
1.30 – 3.00 | Health Technology Assessments of AI/ML | Lead | Lead |
3.30 – 5:00 | Building field evidence of AI & ML in health and healthcare | Lead | Lead |
– Impact Assessments/Evaluations of AI/ML | Lead | Lead |
Day 4 – January 17, 2022 | |||
Timing | Topic | India Faculty | UK Faculty |
9.30 – 11.00 | Ethical development & use of AI/ML in health and healthcare | Co-Lead | Co-Lead |
11.30 – 12.30 | Ethical data sharing mechanisms | Co-Lead | Co-Lead |
1.30 – 3.00 | Regulatory aspects for AI/ML in health and healthcare | Co-Lead | Co-Lead |
3.30 – 5:00 | Improving clinician acceptance and workforce expertise on use of AI/ML in health and healthcare | Co-Lead | Co-Lead |
Day 5 – January 18, 2022 | |||
Timing | Topic | India Faculty | UK Faculty |
9.30 – 11.00 | Group exercise: Developing a business case of AI/ML in hospital or public health setting | India | UK |
11.30 – 12.30 | Group exercise: Developing a business case of AI/ML in hospital or public health setting | India | UK |
1.30 – 3.00 | Presentations from groups | India | UK |
3.30 – 5:00 | Feedback, Group photo, certificates | India | UK |
Will be updated soon!
Will be updated soon!
The workshop will have a hybrid format involving both virtual and face to face sessions. We are looking to work with 20 early career researchers (ECRs) who will take part in this five day workshop program, which will take place between January 14 – 18, 2022. The researchers from India will be joined by 10 ECRs from the UK who will participate online. All participants will be mentored by experts from Amrita Institute of Medical Sciences & Research Center.
The smaller number of ECR participants from the UK has been deliberately chose to allow better online interactions and appropriate levels of mentoring. Our aim is to conduct the workshop so that there is the opportunity for all ECRs from India and the UK to discuss and share learning.
The workshop is comprised of a series of sessions each of which covers key concepts and issues. Each session will be led by an Expert from both India and the UK who will actively work to encourage full participation from all attendees.
Following the workshop, the UK and Indian participants will be asked to work in groups to complete a literature review on a theme with a view to identify gaps and opportunities that a future research proposal could address. To facilitate this, all the UK and India early career researchers will be supported with seed grants.
To support ongoing engagement and continued partnership, all workshop materials will be made available from this website.
Amrita School of Medicine
Amrita Vishwa Vidyapeetham,
AIMS Health Sciences Campus,
AIMS Ponekkara P. O.
Kochi, Kerala – 682 041
India