Ai in Healthcare Industry
                     AI in Healthcare Industry 
Source: https://proquantic.com/
AI’s transformative influence in 
modernizing global healthcare
• AI benefits the practitioner by efficiently providing the 
physician with qualitative and quantitative data based on 
input feedback.
• AI's ability to' learn' from data allows it to improve its 
accuracy based on feedback responses.
• AI systems in healthcare work in real-time.
• The assembled data consists of various demographics, 
physical exams, lab images, electronic recordings from 
multiple notes, and numerous medical notes.
Leveraging AI for targeted diagnostics
Structured learning
• Modern deep learning 
• Neural network system 
• Machine learning 
Unstructured learning
• Forecasting injuries
• Predictive analytics
• Detecting early signs
• Treatment and research
• Remote monitoring
AI pinpointing impending health risks – key 
applications 
• Detecting early signs of stroke 
• Forecasting kidney injuries 
• Cancer treatment and research
• Predictive analytics 
• Remote monitoring 
Ethical considerations and current limitations 
• AI has to put human rights and ethics at the core of design, and use. 
• AI depends on a vast pool of patient data that ensures 
confidentiality and security. 
• AI algorithms can produce biased data if the database is not 
diversified.
• This can create healthcare disparities, hampering accurate 
treatments.
The future contours of AI in healthcare 
• AI has the potential to revolutionize patient care, leading to better 
outcomes and a more efficient healthcare system, inspiring hope for 
the future of medicine. 
• AI will empower healthcare practitioners to provide tailored care to 
each patient.
• AI reassures the audience about the personalization of healthcare, 
resulting in a more efficient healthcare system and better 
outcomes.
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