AI is an advanced filed, involve in different discipline, the future ruler will be AI (artificial intelligence)! decide what you want an human made AI or a human in the society.

1. ARTIFICIAL
INTELLIGENCE
PRESENTER:
CHANDANA K
MSc SYSTEMS BIOLOGY
Manipal School of Life Science

4. 5
4
3
2
1
1. Types of AI
2. Components of AI
3. General Application
4. Application in medicine
5. Discussion and conclusion
Brief about
artificial intelligence

5. TYPES OF
ARTIFICIAL
INTELLIGENCE
https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence
SELF AWARNESS
THEORY OF MIND
BASED ON CAPABILITIES BASED ON FUNCTIONALITIES
NARROW AI
SUPER AI
GENERAL AI REACTIVE MACHINE
LIMITED MEMORY

6. TYPES OF
ARTIFICIAL
INTELLIGENCE
https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence
SELF AWARNESS
THEORY OF MIND
BASED ON CAPABILITIES BASED ON FUNCTIONALITIES
NARROW AI
SUPER AI
GENERAL AI REACTIVE MACHINE
LIMITED MEMORY

7. Component of AI
Application
• Image recognition
• Speech recognition
• Chatbots
• Natural language generation
• Sentiment analysis
Types of model
• Deep learning
• Machine learning
• Neural network
Software / hardware for training and
running models
• GPUs
• Parallel processing tools (like spark)
• Cloud data storage and compute
platforms
Programming language for building
models
• Python
• TensorFlow
• Java
• c

8. General Application

9. Application in medicine
 Cardiology
• Atrical fibrillation
• Cardiovascular risk
 Pulmonary medicine
 Endocrinology
 Nephrology
 Gastroenterology
 Neurology
• Epilepsy
• Gait, posture, and tremor
assessment
 Computating diagnosis of cancer
in histopatology
 Medical imaging and validation
of AI- based technologies

10. Cardiology
Atrial fibrillation
• Stroke
• AliveCor - FDA approval
• Apple – FDA approval
Cardiovascular risk
• Acute coronary syndrome
• Heart failure

11. pulmonary medicine
and Endocrinology
• Pulmonary functional test
spirometry
• Glucose monitoring - Guardian system
• Medtronic - FDA- Guardian system
• Watson (AI developed by IBM)

12. Nephrology
and gastroenterology
• Better Immunoglobulin A
Nephropathy Prediction
Models.
• Better Acute Kidney Injury
Prediction Models.
• Convolutional neural networks among
other deep learning models
• Detects abnormal structure such as
colonic polyps.
• Used in diagnosis of various diseases.

13. Neurology
Epilepsy
• Empatica received FDA approval in
2018 for their wearable Embrace.
Gait, posture, and tremor
assessment

14. Computational diagnosis of
cancer in histopatology

15. Discussion and conclusion
1. Validation of AI – based technologies : toward a
replication crisis?
2. Ethical implications of ongoing monitoring
3. The need of educate augmented doctors
4. The promise of ambient clinical intelligence : avoiding
dehumanization by technology
5. Why doctors be replaced by artificial intelligence?

16. Pros
Cons

17. Reference
1. Bruno E, Simblett S, Lang A, Biondi A, Odoi C, Schulze-Bonhage A, et al. Wearable technology in epilepsy: the
views of patients, caregivers, and healthcare professionals. Epilep Behav. (2018) 85:141–9. doi:
10.1016/j.yebeh.2018.05.044 43.
2. Christiansen MP, Garg SK, Brazg R, Bode BW, Bailey TS, Slover RH, et al. Accuracy of a fourth-generation
subcutaneous continuous glucose sensor. Diabet Technol Therapeut. (2017) 19:446–56. doi:
10.1089/dia.2017.0087.
3. Dorsey ER, Glidden AM, Holloway MR, Birbeck GL, Schwamm LH. Teleneurology and mobile technologies: the
future of neurological care. Nat Rev Neurol. (2018) 14:285–97. doi: 10.1038/nrneurol.2018.31.
4. Halcox JPJ, Wareham K, Cardew A, Gilmore M, Barry JP, Phillips C, et al. Assessment of remote heart rhythm
sampling using the AliveCor heart monitor to screen for atrial fibrillation: the REHEARSE-AF study. Circulation.
(2017) 136:1784–94. doi: 10.1161/CIRCULATIONAHA.117.030583.
5. Lawton J, Blackburn M, Allen J, Campbell F, Elleri D, Leelarathna L, et al. Patients’ and caregivers’ experiences of
using continuous glucose monitoring to support diabetes self-management: qualitative study. BMC Endocrine
Disord. (2018) 18:12. doi: 10.1186/s12902-018-0239-1.
6. Niel O, Bastard P. Artificial intelligence in nephrology: core concepts, clinical applications, and perspectives. Am J
Kidney Dis. (2019) 74:803–10. doi: 10.1053/j.ajkd.2019.05.020 32.
7. Yang YJ, Bang CS. Application of artificial intelligence in gastroenterology. World J Gastroenterol. (2019) 25:1666–
83. doi: 10.3748/wjg.v25.i14.1666.