ARTIFICIAL INTELLIGENCE

What is AI or Artificial Intelligence?

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially
computer systems. These processes include learning (the acquisition of information and rules for using the
information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular
applications of AI include expert systems, speech recognition and machine vision.

AI also emphasizes the creation of intelligent machines that work and react like humans. Some of the
activities computers with artificial intelligence are designed for include:

 Speech recognition
 Learning
 Planning
 Problem solving

AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that
is designed and trained for a particular task. Virtual personal assistants, such as Apple's Siri, are a form of weak
AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive
abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human
intervention.

Examples of AI or Artificial Intelligence:

 Automation: It is what makes a system or process function automatically. For example, robotic process
automation (RPA) can be programmed to perform high-volume, repeatable tasks that humans normally
performed. RPA is different from IT automation in that it can adapt to changing circumstances.
 Machine learning: The science of getting a computer to act without programming. Deep learning is a
subset of machine learning that, in very simple terms, can be thought of as the automation of predictive
analytics. There are three types of machine learning algorithms:
 Supervised learning: Data sets are labeled so that patterns can be detected and used to label new
data sets
 Unsupervised learning: Data sets aren't labeled and are sorted according to similarities or
differences
 Reinforcement learning: Data sets aren't labeled but, after performing an action or several actions,
the AI system is given feedback
 Machine vision: The science of allowing computers to see. This technology captures and analyzes visual
information using a camera, analog-to-digital conversion and digital signal processing. It is often
compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see
through walls, for example. It is used in a range of applications from signature identification to medical
image analysis. Computer vision, which is focused on machine-based image processing, is often conflated
with machine vision.
 Natural language processing (NLP): The processing of human -- and not computer -- language by a
computer program. One of the older and best known examples of NLP is spam detection, which looks at
the subject line and the text of an email and decides if it's junk. Current approaches to NLP are based on
machine learning. NLP tasks include text translation, sentiment analysis and speech recognition.
 Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often
used to perform tasks that are difficult for humans to perform or perform consistently. They are used in
assembly lines for car production or by NASA to move large objects in space. Researchers are also using
machine learning to build robots that can interact in social settings.
  Self-driving cars: These use a combination of computer vision, image recognition and deep learning to
build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected
obstructions, such as pedestrians.

Uses of AI or Artificial Intelligence:

 AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are
applying machine learning to make better and faster diagnoses than humans. One of the best known
healthcare technologies is IBM Watson. It understands natural language and is capable of responding to
questions asked of it. The system mines patient data and other available data sources to form a hypothesis,
which it then presents with a confidence scoring schema.
 AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed
by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to
uncover information on how to better serve customers. Chatbots have been incorporated into websites to
provide immediate service to customers. Automation of job positions has also become a talking point
among academics and IT analysts.
 AI in education. AI can automate grading, giving educators more time. AI can assess students and adapt
to their needs, helping them work at their own pace. AI tutors can provide additional support to students,
ensuring they stay on track. AI could change where and how students learn, perhaps even replacing some
teachers.
 AI in finance. AI in personal finance applications, such as Mint or Turbo Tax, is disrupting financial
institutions. Applications such as these collect personal data and provide financial advice. Other programs,
such as IBM Watson, have been applied to the process of buying a home. Today, software performs
much of the trading on Wall Street.
 AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans.
Automating this process is a more efficient use of time. Startups are also building question-and-answer
computer assistants that can sift programmed-to-answer questions by examining the taxonomy and
ontology associated with a database.
 AI in manufacturing. This is an area that has been at the forefront of incorporating robots into
the workflow. Industrial robots used to perform single tasks and were separated from human workers, but
as the technology advanced, that changed.

Uses of AI in Medical Field:

 Annotator for clinical data. Around 80 percent of healthcare data is unstructured, and AI can read and
understand unstructured data. AI’s ability to process natural language allows it to read clinical text from
any source and identify, categorize and code medical and social concepts.
 Insights for patient data. Artificial intelligence can identify the problems contained in patients’ historical
medical records – both in the structured and unstructured text. It summarizes the history of their care
around those problems and can provide a cognitive summary of a patient records.
 Patient similarity. AI can identify a measure of clinical similarity between patients. This allows
researchers to create dynamic patient cohorts, rather than static patient cohorts. It also enables an
understanding which care path works better for a given group of patients.
 Medical insights. With AI technologies, researchers can find information in unstructured medical
literature to support hypotheses – helping in the discovery of new insights. AI can read through a complete
set of medical literature, such as Medline, and identify the documents that are semantically related to any
combination of medical concepts.

Examples of AI in Medical Field

  Today, AI technologies such as IBM Watson are being used at Memorial Sloan Kettering Cancer Center
to support diagnosis and create management plans for oncology patients. Watson is accomplishing these
plans by effectively synthesizing millions of medical reports, patient records, clinical trials and medical
journals. Watson’s results are routinely “out-diagnosing” medical residents in certain situations. IBM has
also partnered with CVS Health for chronic disease treatment using AI technology. Johnson & Johnson
and IBM are using AI to analyze scientific papers to find new connections for drug development.
 Other examples of AI currently being used in medicine include patient care in radiology. AI can search
and quickly interpret billions of data points – both text and image data – within the patient’s electronic
medical record. It can do this using other patient similar cases and across the most up-to-date medical
research. AI in healthcare has the potential to improve patient care and staff efficiency by assisting with
medical image analysis and diagnosis. AI has been used in many advanced use cases in oncology to help
detect abnormalities in X-rays and MRIs, in genomics to perform complex processing and in precision
medicine to provide assistance in creating highly customized treatments for individual patients.

AI in Nursing

 Personal health virtual assistant. With most of today's adolescents, adults and seniors owning a
smartphone, they are likely to have access to an intelligent personal virtual assistant on their device. The
likes of Cortana, Siri and Google Assistant are backed by powerful systems with strong AI capabilities.
These systems have the potential to provide tremendous value when combined with healthcare apps.
Healthcare apps can be used to deliver medication alerts, patient education material and human-like
interactions to gauge a patient's current mental state. The application of AI in the form of a personal
assistant can have an incredible impact on monitoring and assisting patients with some of their needs when
clinical personnel are not available.
 Personal life coach. Healthcare providers who treat patients with chronic diseases recognize the
importance of maintaining contact with their patients outside of the exam room. Several hospitals have
introduced life coaching services as part of their overall care, but the cost of such services compared to
the current shrinking reimbursements makes it difficult to sustain such programs. However, with today's
powerful AI capabilities and mobile apps, patients can receive feedback on a number of data elements
captured on their phone or wearable devices. Whether it relates to medication adherence or is simply a
motivational voice that encourages fitness activities and healthy habits, AI as a personal life coach creates
a customized experience for each individual patient and offers proactive alerts that can be sent back to
physicians.
 Healthcare bots. One of the new areas of AI that is beginning to gain adoption is in the field of customer
service, and healthcare bots are likely to be available soon as part of what healthcare providers offer. A
bot is an AI application patients can interact with through a chat window on a website or via telephone to
receive help with their requests. Bots can be used in situations such as scheduling follow-up appointments
with a patient's provider online. Other examples include when a bot helps a patient with their medication
or medical billing needs. These uses of AI in healthcare improve customer service; offer 24/7 assistance
for basic requests, such as scheduling, billing and other clinical requests; and reduce the overall
administrative costs for hospital

QUIZ: IDENTIFICATION

1. A category of AI system that is designed and trained for a particular task.

Answer: WEAK AI or NARROW AI

2. It is an AI technology used in Memorial Sloan Kettering Cancer Center to support diagnosis and create management
plans for oncology patients by synthesizing millions of medical reports, patient records, clinical trials and medical
journals.

Answer: IBM WATSON

3. It is an application of AI that helps in monitoring and assisting patients with some of their needs when clinical
personnel are not available.

Answer: PERSONAL HEALTH VIRTUAL ASSISTANT

4. Through this application of AI in nursing, patients can receive feedbacks on a number of data elements (e.g. medical
adherence and lifestyle) captured on their phone or wearable devices which can also be sent to physicians to serve as
proactive alerts.

Answer: PERSONAL LIFE COACH

5. It is an AI application where patients can interact with through a chat window on a website or via telephone to receive
help with their requests, such as scheduling for follow-up appointments and billing.

Answer: HEALTHCARE BOTS .

6. Bots can be used in situations such as scheduling follow-up appointments with a patient's provider online.

Answer: TRUE

7. Virtual personal assistants, such as Apple's Siri, are a form of weak AI.

Answer: TRUE

8. Around 80 percent of healthcare data is unstructured, and AI can read and understand unstructured data. AI’s
ability to process natural language allows it to read clinical text from any source and identify, categorize and code
medical and social concepts.

Answer: TRUE

9. IBM Watson is being used at Memorial Sloan Kettering Cancer Center to support diagnosis and create
management plans for oncology patients.

Answer: TRUE

10. Cortana, Siri and Google Assistant are examples of personal health virtual assistants.

Answer: TRUE