Health infographic

3 min 12 sec

Use of AI in healthcare

Nurse Average Diagnosis Time

90.2%

77.5%

Decision-making

Individual wellbeing

73.5%

2 min 27 sec

• Technologies (eg. apps) encourage people to live healthier lifestyles and decreases their risk of developing diseases and needing medical attention, giving patients autonomy over their well-being.
• Apps allow carers and nurses to understand the individualised needs of their patients more.

• AI is capable of using data for predictive analysis allowing for faster and more accurate decision-making which is benefitial for the patient's medical outcome.

Doctor Average Diagnosis Time

1 min 7 sec

Computer Average Diagnosis Time

Treatment

Early detection

Main developments

• Diseases are able to be detected early which increases the patient's chance for a good prognosis.
• Repetitive jobs such as counting cancer dividing cells can be done by AI technology.
• Medical wearables and smart watches are also able to detect early heart disease symptoms which allows for faster diagnosis.

• AI can be used to generate individual care plans and treatment strategies based on the patient's data.
• Robots have been used in surgery alongside doctor supervision.
• Robotics are also used in physical rehabilitation centers.

Natural Language Processing

• AI can communicate with each other/other models through a universal language.
• Patient documents, radiology data can be transcribed into a large database.

Diagnosis

Physical Robots

Palliative care

• The time between displaying symptoms and receiving an accurate diagnosis from the doctor is drastially shortened.
• IBM’s “Watson for Health” is a computer that is capable of storing and retrieving the information of all medical case studies and symptom data on the internet.

• Assistants in surgery (minimal invasive, human-assisted approach, stitching)
• Complete manual tasks to make the healthcare sector more efficient (eg. in hospitals).

• Robots can aid with keeping palliative patients happy by mimicking human behaviour (eg. having conversations).
• Robots are could have a positive impact on people in the end stages of their lives.

Machine Learning

• Statistical models that can predict the likelihood of a patient for contracting certain diseases based on applying learnings from previous models and using individual patient data.
• Applied in precision medicine which requires an individual-specific dataset to predict accurate and successful treatment methods.
• “Neural networks” are created within large data sets as machines have the ability to interlink large data sets to form diagnoses for patients.
• Deep learning is the most complex form of AI, and a common application is CAD (computer aided detection) which is used in radiology and oncology to detect early stages of cancer.

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