With the global spread of coronavirus, the medical professionals have become overwhelmed with people coming into emergency rooms for minor symptoms. The sudden increase in the demand of medical services have forced the healthcare providers to revisit their workflow to keep delivering continued Transforming Healthcare in the current situation. Many answers have been given to this problem, but a reoccurring response is the use of artificial intelligence in healthcare.

The flood of medical assistance requests is making many healthcare professionals divert their time away from severely sick patients to Covid-19 assessments, which have been largely negative. With the pandemic asking for dedicated medical efforts, the medical professionals had to put many of their non-urgent consultations on hold. The hospitals modified their infrastructure by dividing their space with Covid and Covid-free areas to prevent patients and staff getting exposed to the virus.

Due to the sudden changes in service requirement, Transforming Healthcare institutions have started adopting digital solutions to streamline and automate their services. Certainly, the Covid-19 pandemic is a catalyst for the monumental shift in the healthcare system.

Technologies are at the rescue for Healthcare

During this pandemic, it became critical for people to self-assess whether they are infected with the virus or not. People started taking appointments with general practitioners over a video or voice call. It helped the healthcare professionals to screen the patients from remote locations. Telemedicine apps like Mdlive made the fight against Covid-19 possible by allowing practitioners to schedule and conduct video conferencing appointments via mobile devices. The purpose was to limit the footfall at hospitals or clinics and reduce the person-to-person interaction.

However, it was nearly impossible for healthcare professionals worldwide to consult every patient personally. To address this issue, apps like Livi made use of AI-powered cognitive healthcare agents, which can help patients in risk-assessment over a web chat or voice call. These AI-powered solutions are capable of analysing symptoms and other risk factors based on the guidelines of WHO or CDC (Disease Control and Prevention). This has helped millions of people to the virus without putting additional load on the healthcare infrastructure.

Top 4 applications of Machine Learning and Artificial Intelligence in Healthcare

It has been seen that AI and ML technologies have enormous possibilities in the healthcare sector. Here I’m breaking down the applications of AI and ML, which are being used to revamp the healthcare infrastructure.

Automated Research

When it comes to disease research and treatments, it is not possible to overstate how broad the world of Transforming Healthcare is. For a century, universities and labs around the world have been researching the cure and prevention for existing as well as potential diseases. Connecting and synchronising all of the research can potentially result in making the research faster and more meaningful.

As the time passes, more and more research is being published and it becomes tough for the medical practitioners and pharma companies to stay tuned with them. Systematic reviews are conducted by bringing data together from several different studies. But, these reviews are painstakingly labour intensive and often take years to compile the data and summarise.

artificial intelligence in healthcare

In December 2018, Cochrane community, British international charitable organisation for medical research findings, in collaboration with Microsoft, conducted a project named ‘Project Transform’. The project was aimed at conducting systematic reviews using AI technology to boost the process of systematic reviews.

The medical researches can also leverage the potential of Machine Learning technology to analyse trail reports by automating the literature search using ‘text mining’. The AI technology can help in identifying, categorising, and inspecting thousands of randomised trials to find the appropriate ones for systematic reviews. By using the AI and ML technology, the Project Transform by Cochrane community realised 60-80% reduction in their research efforts.

One of the biggest breakthroughs of AI in drug research and development occurred in 2007 when the medical researchers used a robotic software named ‘Adam’, which had researching functions of yeast, to analyse billions of data sets in public domain in order to hypothesize about the function of 19 genes in the yeast. The software algorithm predicted 9 new hypotheses which were accurate.

Examples of using AI for medical research and development:

BioXcel Therapeutics

BioXcel works in the field of immuno-oncology and neuroscience. The company usages AI technology in its drug re-innovation program where they use the technology to find new applicants for new patient identification and identify new applications for existing drugs. The BioXcel Therapeutics was named among the “Most Innovative healthcare AI Developments of 2019.”

BERG Health

BERG is a biotech platform that utilises Artificial Intelligence to discover breakthroughs in drug development. BERG combines its interrogative biology approach with the traditional research and development process, which makes it capable of developing very reliable drugs for rare diseases.

Recently, BERG used AI to find links between chemicals in the human body which were unknown previously. They presented their findings at the Neuroscience conference in 2018.

Automation of Both External and Internal Communication

The AI and ML technologies’s participation in Transforming Healthcare communication involves both internal communication between healthcare institutions and external communication with patients. Modern AI-powered chatbots and virtual assistants are capable of communicating with the patients, even for complex communication such as organ referrals, offerings, and allocation.

artificial intelligence in healthcare

For external communication purposes, the AI and ML technologies are used for both healthcare marketing and patient care. The AI-powered software solutions can help the patients to seek online consultation with cognitive healthcare representatives. There are many more other possibilities for AI and ML to improve patient care including telemedicine.

Today, the technologies are also used to help medical institutions, pharma companies, and practitioners to present themselves to the public. However, marketing has never been considered as the major influencing factor in the healthcare sector, still it has its role to play. It is due to the branding and advertising efforts, that the patients know which name to trust upon and seek consultation or treatment from.

Also, the healthcare sector can make use of Machine Learning technology to gather and analyse the data, which can help them in moving to the right direction in order to make services available. The healthcare sector has to shift their focus to where the need is. This approach means that the technologies will enable healthcare institutions to better reach the patients that will require most assistance.

Examples of using AI for patient communication:

Buoy Health

Buoy Health is a Boston based symptom and cure checker software application that utilizes AI technology to diagnose and treat illness. It makes use of Chatbots to conversate with the patient to identify symptoms and health related concerns. The chatbot will listen to the patients and guide them to improvise the care based on the diagnosis. Harvard Medical School is using Buoy’s AI application to diagnose and treat patients in less time.

Diagnostics 2.0

Quickly and accurately diagnosing the issue is very crucial for the healthcare sector. Think of a situation where some people brought an elderly person into the hospital’s emergency department after he fell down the stairs. The patient complains of a headache, but it doesn’t look severe. Unfortunately, it is Friday, a huge footfall at the local emergency room. There are already 90 patients in the radiologist’s appointment list and it will be a two-hour wait before the doctor finds out the patient’s pulmonary embolism on the scans.

Fortunately, the technologies are getting at the core of this area of medical services. After the years of data collected via digitizing the patients records, the healthcare sector has a pool of data that is still growing. Using this data with analytical tools powered by machine learning can make it possible to detect disease like pulmonary embolism or cancer at a very early stage.

Examples of using AI for better diagnosis:

PathAI

PathAI is developing machine learning technology with a goal to assist pathologies in more accurate diagnoses. The company is working on reducing errors in cancer diagnosis and also finding methods for medical treatment for individuals.

The company has worked with drug developing organisations like Bristol-Myers Squibb and Bill & Melinda Gates Foundation to make use of its AI & ML technology into other different healthcare industry verticals.

Enlitic

Enlitic is a tool to streamline the radiology diagnosis. It’s deep learning platform structures the unstructured medical data to provide medical practitioners with meaningful insight to the patient’s medical condition. The data includes blood tests, radiology images, genomics, historical medical records, EKGs etc.

Beth Israel Deaconess Medical Center

The teaching hospital of Harvard University, Beth Israel Deaconess Medical Center, has implemented AI for proactively diagnosing deadly diseases related to blood. Doctors use AI-enhanced microscopes that can quickly scan harmful bacterias like staphylococcus and E. coli in the blood samples. It takes very less time than manual scanning. The hospital says that to teach machines how to search for bacteria, they’ve fed the AI-powered machines with 25,000 images of blood samples. Currently the machines are 95% accurate in identifying and predicting harmful bacteria in blood.

Advanced Treatment

The applications of AI and ML in healthcare are going beyond scanning health records or streamlining the workflow. These technologies can help medical practitioners identify chronically ill patients who are more likely to be at a risk of an adverse episode. AI can help practitioners by encouraging a comprehensive approach for disease management and allowing them to to better coordinate healthcare plans.

Not only the doctors, but also the patients can leverage AI to stay in tune with their treatment plans. The healthcare mobile apps can remind the patients of their medication, schedule appointments with the particular doctor, track the health status using IoMT devices, and consult doctors via video conferencing, share reports via chat. All of it cumulatively will upgrade the medical treatments to an improved level.

Examples of using Artificial Intelligence in healthcare for better diagnosis:

Babylon Health

Babylon makes use of artificial intelligence technology to improve the patient’s treatment. It allows the patients to book face-to-face appointments with the doctors. Also, the patients can interact with the AI-powered chatbot that is capable of screening the patients based on their primary symptoms. Based on the analysis, the chatbot will also recommend the patient for either a face-to-face visit or virtual check-in. 

Cleveland Clinic

A hospital based out of Cleveland, Ohio, Cleveland Clinic teamed up with IBM to leverage IT capabilities especially AI in healthcare operations. The hospital is making use of artificial intelligence to gather information from a pool of patient health and administrative data records. They utilize this data to streamline their healthcare services for the patients. The combination of data analytics and artificial intelligence in healthcare is helping Cleveland Clinic to personalise their Transforming Healthcare plans based on the market demand.

Conclusion

The applications of artificial intelligence and machine learning in the healthcare sector are limitless. The ones we’ve discussed in the article are those which are very popular nowadays. Of course, there are other technologies that are revolutionizing the Transforming Healthcare services. For example, the Internet of Medical Things devices are helping healthtech developers to build reliable solutions for remote health monitoring. 

We, at Nimble AppGenie are currently working on deploying AI enabled chatbots and virtual solutions in the Transforming Healthcare sector. If you are looking for a development service provider specialised in the healthcare sector, feel free to contact us at contact@nimbleappgenie.com 

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