Artificial intelligence and machine learning in healthcare are pulling a huge amount of funds and attention in the past few years. Global technological leaders are shifting their gears and accelerating their artificial intelligence research in the medical field. Google’s Deepmind also want to try their hands in the medical field applications after winning the much talked Go tournament.

Even the artificial intelligence startups are making an effort to provide solutions to the healthcare. For example AI startup Ayasdi has a turnover of $94MM, made total revenue of $144MM and Digital Reasoning Systems raised $36MM. Investors are willing to invest heavily in the medical artificial intelligence applications because they are well aware of big profits and a huge Return on Investment (RoI) of the medical field.

According to a report of World Health Organization Report, by 2020 the chances of getting the chronic disease may increase by up to 57%. But the latest advancements in machine learning services will improve the treatment and the cost of treatment will also be reduced. Some of the artificial intelligence advancements are proteomics, cell biology, stem cell, organ biology and robotic surgery.

During the past few years, the some of the top-notch advancements in the medical field includes:

Artificial intelligence applications include the creation of an artificial pancreas that can sense and adjust the insulin level of the patient.

3D printing of the human body part that can procreate blood vessels and skin that can heal the wound quickly.

Artificial intelligence eyes enable blind people to see up to a certain extent.

Artificial intelligence based small device that is implanted in the human body to reduce the impact of headaches.

Biomedical advancements in artificial intelligence services include the creation of Graphene, an extremely flexible substance at cheap rates. This has improved the biomedical applications like tissue engineering.

Let us discuss some of the latest AI advancements that are taking place in the Medical field:

Medical Imaging

Digital image processing systems and computer vision have the ability to pinpoint even the smallest of the details in the CT scan reports and Mammogram scans. The improved medical vision development that is solely based on the deep learning and machine learning algorithms that has the ability to accurately detect every sign of any kind of chronic cancer, breast cancer or aortic aneurysms. The deep learning neural networks can be trained by past real-life data to detect the symptoms of the diseases. The accuracy of medical imaging gets improved over the time and almost all life-threatening diseases can be detected at an early stage that can save the lives of millions of patients.

Electronic Media Recording

No doubt Electronic Media recording has revolutionized the Electronic Media records (EMR), it is one of the most controversial topics of discussion in of the last decade. EMR has improved the quality of the healthcare and also has improved the productivity of the medical diagnostic systems also. Due to lack of knowledge and awareness, many of the healthcare providers found it to be hectic and difficult to use. Data science services have helped in developing the AI-enabled software tools that are easy to use and simplify the everyday operations of doctors and physicians.

Virtual Nurses

Virtual Nurses or Virtual Health Assistant (VHA) are able to take care of the patients like any other human nurse. Virtual Health Assistants reminds the patients to take medications on time by sending them notifications. They also keep a check on the medical condition of the patients like heart rate, pulse rate, blood sugar level etc. They also provide the proper diet plan for the patients to follow. They also assist doctors by sending them daily reports about the patient health improvement.

Healthcare Bots

Healthcare bots based applications that can answer the queries of the patients. Patients ask a lot of queries about their medicine, treatment, and health. Healthcare bots help the patients in real time by simply making a conversation with the patients. Bots can suggest the medicines, fix an appointment with the doctor and answer health-related queries of the patients. AI and machine learning healthbots can mimic the human conversation in a most natural way. They can detect the emotions of the humans and can be empathetic with the patients. They are built using Natural Language Processing and can also be used in the data mining process. Computer vision and digital image processing can enable the chatbots to understand photos, handwritten notes, and barcodes.

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Benefits of Artificial intelligence in Healthcare

Artificial intelligence and data science services have improved the treatment, monitoring systems and also reduced the cost of treatment.

Artificial intelligence applications include virtual assistants that handle the patients in real time and patients can get their queries answered instantly.

According to Frost and Sullivan report, deep learning applications have the ability to improve the outcomes by 30-40 percent and cost of treatment is reduced to 50 percent. The improved accuracy and precision have reduced human errors that decrease the number of doctor’s visits.

Why Artificial intelligence is important for healthcare:

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In the upcoming future, artificial intelligence services will affect the medical field massively. The scope of AI machines in healthcare is vast and the while handling the massive amount of data, we can eradicate the causes of almost every disease. Powerful insight can be drawn from the historical medical diagnosis of a patient using data mining services. Healthcare costs will also be reduced to a considerable amount. Although, AI and robotics cannot match the judgment of doctors we can expect AI machines to assist the doctors in an innumerable number of ways in the upcoming future.

Author's Bio: 

Ajay Thakur is working as a Content Marketing Manager in Webtunix Solutions Private Limited. I am very enthusiastic to learn about Machine Learning and Deep Learning techniques. I always express my knowledge to beginners who want to start their career as a Data Scientist.