Question

Q1 Describe one example of (a) how artificial intelligence has been used in healthcare to solve a specific problem. (b) What were some of the challenges the project faced? Q2 Post your Al example and address the following points (a) What was the problem the Al was aiming to solve (b) What did the Al do, and (c) how was it successful?

Answer 1

Q1.Artificial intelligence is the study of computer systems that model and apply the intelligence of the human mind. Artificial intelligence is about systems behaving in a way that is similar to humans behaving intelligently in the same situation.

(a)The integrated artificial intelligence application healthcare sector is its (mobile apps for the info, medical diagnosis, treatment alternatives, patient follow-up, research)

*Diagnosis:

Artificial intelligence has been utilized to improve medical diagnosis. Artificial intelligence aided medical image diagnosis from Beijing-based artificial intelligence high-tech company.

Infervison, is being used to improve reading CT scans and x-rays. The technology, which is used in hospitals in China, can detect suspicious lesions and nodules in lung cancer patients. This allows doctors to provide patients with early diagnosis as opposed to sending tissue samples to a lab for analysis, thereby providing treatments earlier than usual.

Researchers at Stanford University have created an Artificial intelligence algorithm that can identify and diagnose skin cancer. This technology, using images of moles, rashes, and lesions, may someday be available as a mobile app on smartphones.

Google’s parent company, Alphabet, is working on an Artificial intelligence program helps to detect metastasis using high-level image recognition. The program will be able to do this faster than the conventional way, which again translates to earlier diagnosis and treatment.

Furthermore, because Artificial intelligence can analyze large volumes of data it enables the detection of disease and helps with clinical decisions.

Mobile applications:

Bots for healthcare exist primarily for patient engagement. Healthcare bots, which are found in mobile messaging apps, can help patients quickly and in real time simply by sending a message. Health chatbots can answer health-related questions and even help patients manage medications by providing information on types of medications and recommended doses.

Some advancements that have been made in healthcare bots include the ability to:

-Learn and mimic human conversations

-Detect emotions to enable empathetic engagement with patients

-Incorporate Natural Language Processing, sentiment analysis, and concept mining into chat scripts

-Perform complex image recognition tasks to analyze photos, handwritten notes, and barcodes

*Other artificial intelligence solutions being developed in the healthcare field include:

-Heart sound analysis

-Companion robots for the elderly

-Mining medical records

-Design treatment plans

-Assist in repetitive jobs

-Provide consultations

-Drug creation

-Using avatars for clinical training

Advancement in treatments

Artificial intelligence is leading to advancements in healthcare treatments, such as improving the organization of treatment plans, analyzing data to provide better treatment plans, and monitoring treatments.

Artificial intelligence has the ability to quickly and more accurately identify signs of disease in medical images, like MRI, CT scans, ultrasound and x-rays, and therefore allows faster diagnostics reducing the time patients wait for a diagnosis from weeks to mere hours and accelerating the introduction of treatment options.

-Virtual Assistants

In this day and age when people expect to get answers instantly, virtual assistants enable patients to get answers in real time. Patients can ask medical questions and receive answers, get more information and reminders about taking medications, report information to physicians, and gain other medical support. Physicians can also take advantage of healthcare virtual assistants by tracking and following through with orders and making sure they are ordering the correct medication for patients.

*Reduce Costs

Helps to reduce the cost of treatment by as much as 50%. Improvements in precision and efficiency mean fewer human errors, leading to a decrease in doctor visits. Doctors are also able to get information from data for patients who are at risk of certain diseases to prevent hospital re-admissions.

*Treatment Plans

Another benefit of Artificial intelligence in healthcare is the ability to design treatment plans. Doctors can now search a database, such as Modernizing Medicine, a medical assistant used to collect patient information, record diagnoses, order tests, and prescriptions and prepare billing information. Moreover, the ability to search public databases with information from thousands of doctors and patient cases can help physicians administer better-personalized treatments or find comparable cases.

(b) Some of the challenges faced for artificial intelligence in health care:

-Adoption

One of the challenges Artificial intelligence faces in healthcare is widespread clinical adoption. To realize the value of Artificial intelligence, the healthcare industry needs to create a workforce that is knowledgeable about Artificial intelligence so they are comfortable using Artificial intelligence technologies thereby enabling the Artificial intelligence technologies to “learn” and grow smarter.

-Training Doctors/Patients

Another challenge is training doctors and patients to use AI. Learning how to use technology may be a challenge for some. Likewise, not everyone is open to information given by a “robot.” In other words, accepting AI technology is a challenge that needs to be addressed through education.

-Regulations

Complying with regulations is also a challenge for Artificial intelligence in the healthcare industry. For one, there is the need for approvals from FDA before an Artificial intelligence device or application is applied to health care. This is especially true because Artificial intelligence is at a developing stage and not a technology that is fully known or understood. Moreover, the existing approval process deals more with Artificial hardware and not about data. Therefore, data from Artificial intelligence poses a new regulatory challenge for FDA and needs to be validated more thoroughly.

Q2.

-Accuracy and Safety

Since Artificial intelligence is fairly new, it has the potential to be less accurate and reliable thereby putting patients at risk. The BBC article, The Real Risk of Artificial Intelligence addresses this:

“Take a system trained to learn which patients with pneumonia had a higher risk of death so that they might be admitted to hospital. It inadvertently classified patients with asthma as being at lower risk. This was because, in normal situations, people with pneumonia and a history of asthma go straight to intensive care and therefore get the kind of treatment that significantly reduces their risk of dying. The machine learning took this to mean that asthma + pneumonia = lower risk of death.”

Furthermore, Artificial intelligence has to be reliable enough to keep sensitive data, like addresses and financial and health information secure. Institutions that handle sensitive medical information need to make sure their sharing policies keep information safe.